compress_good_bad.txt

1910.00370	Sub-Architecture Ensemble Pruning in Neural Architecture Search	Machine Learning (cs.LG)	Yijun Bian, Qingquan Song, Mengnan Du, Jun Yao, Huanhuan Chen, Xia Hu
1910.00700	NESTA: Hamming Weight Compression-Based Neural Proc. Engine	Machine Learning (cs.LG)	Ali Mirzaeian, Houman Homayoun, Avesta Sasan
1910.00762	Accelerating Deep Learning by Focusing on the Biggest Losers	Machine Learning (cs.LG)	Angela H. Jiang, Daniel L.-K. Wong, Giulio Zhou, David G. Andersen, Jeffrey Dean, Gregory R. Ganger, Gauri Joshi, Michael Kaminksy, Michael Kozuch, Zachary C. Lipton, Padmanabhan Pillai
1910.01108	DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter	Computation and Language (cs.CL)	Victor Sanh, Lysandre Debut, Julien Chaumond, Thomas Wolf
1910.01196	Accelerating Data Loading in Deep Neural Network Training	Machine Learning (cs.LG)	Chih-Chieh Yang, Guojing Cong
1910.01255	Distillation $\approx$ Early Stopping? Harvesting Dark Knowledge Utilizing Anisotropic Information Retrieval For Overparameterized Neural Network	Machine Learning (stat.ML)	Bin Dong, Jikai Hou, Yiping Lu, Zhihua Zhang
1910.01348	On the Efficacy of Knowledge Distillation	Machine Learning (cs.LG)	Jang Hyun Cho, Bharath Hariharan
1910.01740	AntMan: Sparse Low-Rank Compression to Accelerate RNN inference	Machine Learning (cs.LG)	Samyam Rajbhandari, Harsh Shrivastava, Yuxiong He
1910.01769	Distilling Transformers into Simple Neural Networks with Unlabeled Transfer Data	Computation and Language (cs.CL)	Subhabrata Mukherjee, Ahmed Hassan Awadallah
1910.02115	Privacy Preserving Stochastic Channel-Based Federated Learning with Neural Network Pruning	Machine Learning (cs.LG)	Rulin Shao, Hui Liu, Dianbo Liu
1910.02551	Improving Dataset Distillation	Machine Learning (cs.LG)	Ilia Sucholutsky, Matthias Schonlau
1910.02558	Pushing the limits of RNN Compression	Machine Learning (cs.LG)	Urmish Thakker, Igor Fedorov, Jesse Beu, Dibakar Gope, Chu Zhou, Ganesh Dasika, Matthew Mattina
1910.02747	Deep Neural Network Compression for Image Classification and Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Georgios Tzelepis, Ahraz Asif, Saimir Baci, Selcuk Cavdar, Eren Erdal Aksoy
1910.03197	Accelerating Federated Learning via Momentum Gradient Descent	Machine Learning (cs.LG)	Wei Liu, Li Chen, Yunfei Chen, Wenyi Zhang
1910.03539	Pruning Algorithms for Low-Dimensional Non-metric k-NN Search: A Case Study	Information Retrieval (cs.IR)	Leonid Boytsov, Eric Nyberg
1910.03581	FedMD: Heterogenous Federated Learning via Model Distillation	Machine Learning (cs.LG)	Daliang Li, Junpu Wang
1910.03723	Knowledge Distillation from Internal Representations	Computation and Language (cs.CL)	Gustavo Aguilar, Yuan Ling, Yu Zhang, Benjamin Yao, Xing Fan, Edward Guo
1910.04576	Trained Rank Pruning for Efficient Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Yuhui Xu, Yuxi Li, Shuai Zhang, Wei Wen, Botao Wang, Wenrui Dai, Yingyong Qi, Yiran Chen, Weiyao Lin, Hongkai Xiong
1910.04641	Cross-modal knowledge distillation for action recognition	Computer Vision and Pattern Recognition (cs.CV)	Fida Mohammad Thoker, Juergen Gall
1910.04732	Structured Pruning of Large Language Models	Computation and Language (cs.CL)	Ziheng Wang, Jeremy Wohlwend, Tao Lei
1910.04796	DBCSR: A Library for Dense Matrix Multiplications on Distributed GPU-Accelerated Systems	Distributed, Parallel, and Cluster Computing (cs.DC)	Ilia Sivkov, Alfio Lazzaro, Juerg Hutter
1910.04877	Bit Efficient Quantization for Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Prateeth Nayak, David Zhang, Sek Chai
1910.05054	Green Deep Reinforcement Learning for Radio Resource Management: Architecture, Algorithm Compression and Challenge	Machine Learning (cs.LG)	Zhiyong Du, Yansha Deng, Weisi Guo, Arumugam Nallanathan, Qihui Wu
1910.05057	Improving Generalization and Robustness with Noisy Collaboration in Knowledge Distillation	Machine Learning (cs.LG)	Elahe Arani, Fahad Sarfraz, Bahram Zonooz
1910.05422	SiPPing Neural Networks: Sensitivity-informed Provable Pruning of Neural Networks	Machine Learning (cs.LG)	Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus
1910.05872	Rethinking Data Augmentation: Self-Supervision and Self-Distillation	Machine Learning (cs.LG)	Hankook Lee, Sung Ju Hwang, Jinwoo Shin
1910.05897	Learning Sparsity and Quantization Jointly and Automatically for Neural Network Compression via Constrained Optimization	Machine Learning (cs.LG)	Haichuan Yang, Shupeng Gui, Yuhao Zhu, Ji Liu
1910.06360	Pruning a BERT-based Question Answering Model	Computation and Language (cs.CL)	J.S. McCarley
1910.06591	SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference	Machine Learning (cs.LG)	Lasse Espeholt, Raphaël Marinier, Piotr Stanczyk, Ke Wang, Marcin Michalski
1910.06720	Distilled embedding: non-linear embedding factorization using knowledge distillation	Computation and Language (cs.CL)	Vasileios Lioutas, Ahmad Rashid, Krtin Kumar, Md Akmal Haidar, Mehdi Rezagholizadeh
1910.07561	A Double Residual Compression Algorithm for Efficient Distributed Learning	Machine Learning (cs.LG)	Xiaorui Liu, Yao Li, Jiliang Tang, Ming Yan
1910.07939	A Stochastic Variance Reduced Nesterov's Accelerated Quasi-Newton Method	Machine Learning (cs.LG)	Sota Yasuda, Shahrzad Mahboubi, S. Indrapriyadarsini, Hiroshi Ninomiya, Hideki Asai
1910.08237	Mirror Descent View for Neural Network Quantization	Machine Learning (cs.LG)	Thalaiyasingam Ajanthan, Kartik Gupta, Philip H. S. Torr, Richard Hartley, Puneet K. Dokania
1910.08381	Model Compression with Two-stage Multi-teacher Knowledge Distillation for Web Question Answering System	Computation and Language (cs.CL)	Ze Yang, Linjun Shou, Ming Gong, Wutao Lin, Daxin Jiang
1910.08906	Self-Adaptive Network Pruning	Machine Learning (cs.LG)	Jinting Chen, Zhaocheng Zhu, Cheng Li, Yuming Zhao
1910.09152	A New Framework for Multi-Agent Reinforcement Learning -- Centralized Training and Exploration with Decentralized Execution via Policy Distillation	Machine Learning (cs.LG)	Gang Chen
1910.09158	Implementation of a modified Nesterov's Accelerated quasi-Newton Method on Tensorflow	Machine Learning (cs.LG)	S. Indrapriyadarsini, Shahrzad Mahboubi, Hiroshi Ninomiya, Hideki Asai
1910.09177	A Complexity Efficient DMT-Optimal Tree Pruning Based Sphere Decoding	Signal Processing (eess.SP)	Mohammad Neinavaie, Mostafa Derakhtian, Negar Daryanavardan, Sergiy Vorobyov
1910.09318	Directed-Weighting Group Lasso for Eltwise Blocked CNN Pruning	Computer Vision and Pattern Recognition (cs.CV)	Ke Zhan, Shimiao Jiang, Yu Bai, Yi Li, Xu Liu, Zhuoran Xu
1910.09347	Approximate Sampling using an Accelerated Metropolis-Hastings based on Bayesian Optimization and Gaussian Processes	Machine Learning (cs.LG)	Asif J. Chowdhury, Gabriel Terejanu
1910.09455	Depth-wise Decomposition for Accelerating Separable Convolutions in Efficient Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Yihui He, Jianing Qian, Jianren Wang
1910.10032	GPU-Accelerated Viterbi Exact Lattice Decoder for Batched Online and Offline Speech Recognition	Computation and Language (cs.CL)	Hugo Braun, Justin Luitjens, Ryan Leary
1910.10699	Contrastive Representation Distillation	Machine Learning (cs.LG)	Yonglong Tian, Dilip Krishnan, Phillip Isola
1910.11144	A Comparative Study of Neural Network Compression	Machine Learning (cs.LG)	Hossein Baktash (CRISAM, SUT), Emanuele Natale (COATI), Laurent Viennot (GANG)
1910.12061	Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework	Machine Learning (cs.LG)	Srinidhi Hegde, Ranjitha Prasad, Ramya Hebbalaguppe, Vishwajith Kumar
1910.12232	Neural Network Distiller: A Python Package For DNN Compression Research	Machine Learning (cs.LG)	Neta Zmora, Guy Jacob, Lev Zlotnik, Bar Elharar, Gal Novik
1910.12295	MOD: A Deep Mixture Model with Online Knowledge Distillation for Large Scale Video Temporal Concept Localization	Computer Vision and Pattern Recognition (cs.CV)	Rongcheng Lin, Jing Xiao, Jianping Fan
1910.12727	Layer Pruning for Accelerating Very Deep Neural Networks	Machine Learning (cs.LG)	Weiwei Zhang, Changsheng chen, Xuechun Wu, Jialin Gao, Di Bao, Jiwei Li, Xi Zhou
1910.12828	Blind Robust 3-D Mesh Watermarking based on Mesh Saliency and QIM quantization for Copyright Protection	Multimedia (cs.MM)	Mohamed Hamidi, Aladine Chetouani, Mohamed El Haziti, Mohammed El Hassouni, and Hocine Cherifi
1910.13372	Gait Event Detection in Tibial Acceleration Profiles: a Structured Learning Approach	Machine Learning (cs.LG)	Pieter Robberechts, Rud Derie, Pieter Van den Berghe, Joeri Gerlo, Dirk De Clercq, Veerle Segers, Jesse Davis
1910.13618	Optimal Analysis of Subset-Selection Based L_p Low Rank Approximation	Machine Learning (cs.LG)	Chen Dan, Hong Wang, Hongyang Zhang, Yuchen Zhou, Pradeep Ravikumar
1910.13930	Distilling Black-Box Travel Mode Choice Model for Behavioral Interpretation	Machine Learning (stat.ML)	Xilei Zhao, Zhengze Zhou, Xiang Yan, Pascal Van Hentenryck
1910.14226	Distilling Pixel-Wise Feature Similarities for Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Yuhu Shan
1910.14315	BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systems	Machine Learning (cs.LG)	Jiawei Shao, Jun Zhang
1911.00208	LFZip: Lossy compression of multivariate floating-point time series data via improved prediction	Signal Processing (eess.SP)	Shubham Chandak, Kedar Tatwawadi, Chengtao Wen, Lingyun Wang, Juan Aparicio, Tsachy Weissman
1911.00216	On Distributed Quantization for Classification	Machine Learning (cs.LG)	Osama A. Hanna, Yahya H. Ezzeldin, Tara Sadjadpour, Christina Fragouli, Suhas Diggavi
1911.00400	Sparsely Activated Networks: A new method for decomposing and compressing data	Machine Learning (cs.LG)	Paschalis Bizopoulos
1911.00527	Memory Requirement Reduction of Deep Neural Networks Using Low-bit Quantization of Parameters	Audio and Speech Processing (eess.AS)	Niccoló Nicodemo, Gaurav Naithani, Konstantinos Drossos, Tuomas Virtanen, Roberto Saletti
1911.00822	Comprehensive SNN Compression Using ADMM Optimization and Activity Regularization	Neural and Evolutionary Computing (cs.NE)	Lei Deng, Yujie Wu, Yifan Hu, Ling Liang, Guoqi Li, Xing Hu, Yufei Ding, Peng Li, Yuan Xie
1911.01226	Human-centric Metric for Accelerating Pathology Reports Annotation	Computation and Language (cs.CL)	Ruibin Ma, Po-Hsuan Cameron Chen, Gang Li, Wei-Hung Weng, Angela Lin, Krishna Gadepalli, Yuannan Cai
1911.01654	Detecting Point Outliers Using Prune-based Outlier Factor (PLOF)	Machine Learning (cs.LG)	Kasra Babaei, ZhiYuan Chen, Tomas Maul
1911.01699	Reversible Data Hiding in Encrypted Images based on Pixel Prediction and Bit-plane Compression	Multimedia (cs.MM)	Zhaoxia Yin, Yinyin Peng, Youzhi Xiang
1911.02079	Post-Training 4-bit Quantization on Embedding Tables	Machine Learning (cs.LG)	Hui Guan, Andrey Malevich, Jiyan Yang, Jongsoo Park, Hector Yuen
1911.02237	Localization-aware Channel Pruning for Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Zihao Xie, Wenbing Tao, Li Zhu, Lin Zhao
1911.02497	A Programmable Approach to Model Compression	Machine Learning (cs.LG)	Vinu Joseph, Saurav Muralidharan, Animesh Garg, Michael Garland, Ganesh Gopalakrishnan
1911.02639	Word Embedding Algorithms as Generalized Low Rank Models and their Canonical Form	Computation and Language (cs.CL)	Kian Kenyon-Dean
1911.02727	Understanding Knowledge Distillation in Non-autoregressive Machine Translation	Computation and Language (cs.CL)	Chunting Zhou, Graham Neubig, Jiatao Gu
1911.03080	Deep geometric knowledge distillation with graphs	Machine Learning (cs.LG)	Carlos Lassance, Myriam Bontonou, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega
1911.03388	A different take on the best-first game tree pruning algorithms	Artificial Intelligence (cs.AI)	Ishan Srivastava
1911.03462	Knowledge Distillation for Incremental Learning in Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Umberto Michieli, Pietro Zanuttigh
1911.03572	DZip: improved general-purpose lossless compression based on novel neural network modeling	Machine Learning (cs.LG)	Mohit Goyal, Kedar Tatwawadi, Shubham Chandak, Idoia Ochoa
1911.03588	Attentive Student Meets Multi-Task Teacher: Improved Knowledge Distillation for Pretrained Models	Computation and Language (cs.CL)	Linqing Liu, Huan Wang, Jimmy Lin, Richard Socher, Caiming Xiong
1911.03829	Distilling the Knowledge of BERT for Text Generation	Computation and Language (cs.CL)	Yen-Chun Chen, Zhe Gan, Yu Cheng, Jingzhou Liu, Jingjing Liu
1911.03852	HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Zhen Dong, Zhewei Yao, Yaohui Cai, Daiyaan Arfeen, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
1911.04453	Structural Pruning in Deep Neural Networks: A Small-World Approach	Machine Learning (cs.LG)	Gokul Krishnan, Xiaocong Du, Yu Cao
1911.04477	A Computing Kernel for Network Binarization on PyTorch	Machine Learning (cs.LG)	Xianda Xu, Marco Pedersoli
1911.04654	Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search	Information Retrieval (cs.IR)	Xinyan Dai, Xiao Yan, Kelvin K. W. Ng, Jie Liu, James Cheng
1911.04655	Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning	Machine Learning (cs.LG)	Xinyan Dai, Xiao Yan, Kaiwen Zhou, Han Yang, Kelvin K. W. Ng, James Cheng, Yu Fan
1911.04657	CALPA-NET: Channel-pruning-assisted Deep Residual Network for Steganalysis of Digital Images	Multimedia (cs.MM)	Shunquan Tan, Weilong Wu, Zilong Shao, Qiushi Li, Bin Li, Jiwu Huang
1911.04947	Accelerating Training in Pommerman with Imitation and Reinforcement Learning	Machine Learning (cs.LG)	Hardik Meisheri, Omkar Shelke, Richa Verma, Harshad Khadilkar
1911.04951	Iteratively Training Look-Up Tables for Network Quantization	Machine Learning (cs.LG)	Fabien Cardinaux, Stefan Uhlich, Kazuki Yoshiyama, Javier Alonso Garcia, Lukas Mauch, Stephen Tiedemann, Thomas Kemp, Akira Nakamura
1911.05063	Kaolin: A PyTorch Library for Accelerating 3D Deep Learning Research	Computer Vision and Pattern Recognition (cs.CV)	Krishna Murthy Jatavallabhula, Edward Smith, Jean-Francois Lafleche, Clement Fuji Tsang, Artem Rozantsev, Wenzheng Chen, Tommy Xiang, Rev Lebaredian, Sanja Fidler
1911.05248	Selective Brain Damage: Measuring the Disparate Impact of Model Pruning	Machine Learning (cs.LG)	Sara Hooker, Aaron Courville, Yann Dauphin, Andrea Frome
1911.05276	Collaborative Distillation for Top-N Recommendation	Machine Learning (cs.LG)	Jae-woong Lee, Minjin Choi, Jongwuk Lee, Hyunjung Shim
1911.05329	Knowledge Representing: Efficient, Sparse Representation of Prior Knowledge for Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Junjie Liu, Dongchao Wen, Hongxing Gao, Wei Tao, Tse-Wei Chen, Kinya Osa, Masami Kato
1911.05443	Dynamic Connected Neural Decision Classifier and Regressor with Dynamic Softing Pruning	Machine Learning (cs.LG)	Faen Zhang, Xinyu Fan, Hui Xu, Pengcheng Zhou, Yujian He, Junlong Liu
1911.05700	Graph Representation Learning via Multi-task Knowledge Distillation	Machine Learning (cs.LG)	Jiaqi Ma, Qiaozhu Mei
1911.06020	An Accelerated Nonlinear Contrast Source Inversion Scheme For Sparse Electromagnetic Imaging	Signal Processing (eess.SP)	A. I. Sandhu, A. Desmal, H. Bagci
1911.06319	The Canonical Distortion Measure for Vector Quantization and Function Approximation	Machine Learning (cs.LG)	Jonathan Baxter
1911.06786	Stagewise Knowledge Distillation	Machine Learning (cs.LG)	Akshay Kulkarni, Navid Panchi, Shital Chiddarwar
1911.06996	Selective sampling for accelerating training of deep neural networks	Machine Learning (cs.LG)	Berry Weinstein, Shai Fine, Yacov Hel-Or
1911.07190	Loss Aware Post-training Quantization	Machine Learning (cs.LG)	Yury Nahshan, Brian Chmiel, Chaim Baskin, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson
1911.07412	Provable Filter Pruning for Efficient Neural Networks	Machine Learning (cs.LG)	Lucas Liebenwein, Cenk Baykal, Harry Lang, Dan Feldman, Daniela Rus
1911.07471	Preparing Lessons: Improve Knowledge Distillation with Better Supervision	Computer Vision and Pattern Recognition (cs.CV)	Tiancheng Wen, Shenqi Lai, Xueming Qian
1911.07919	ASV: Accelerated Stereo Vision System	Computer Vision and Pattern Recognition (cs.CV)	Yu Feng, Paul Whatmough, Yuhao Zhu
1911.07930	BiNet: Degraded-Manuscript Binarization in Diverse Document Textures and Layouts using Deep Encoder-Decoder Networks	Computer Vision and Pattern Recognition (cs.CV)	Maruf A. Dhali, Jan Willem de Wit, Lambert Schomaker
1911.08019	Online Learned Continual Compression with Stacked Quantization Module	Machine Learning (cs.LG)	Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau
1911.08020	DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks	Machine Learning (cs.LG)	Ao Ren, Tao Zhang, Yuhao Wang, Sheng Lin, Peiyan Dong, Yen-kuang Chen, Yuan Xie, Yanzhi Wang
1911.08076	IFQ-Net: Integrated Fixed-point Quantization Networks for Embedded Vision	Computer Vision and Pattern Recognition (cs.CV)	Hongxing Gao, Wei Tao, Dongchao Wen, Tse-Wei Chen, Kinya Osa, Masami Kato
1911.08114	Neural Network Pruning with Residual-Connections and Limited-Data	Computer Vision and Pattern Recognition (cs.CV)	Jian-Hao Luo, Jianxin Wu
1911.08630	CUP: Cluster Pruning for Compressing Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Rahul Duggal, Cao Xiao, Richard Vuduc, Jimeng Sun
1911.08947	Real-time Scene Text Detection with Differentiable Binarization	Computer Vision and Pattern Recognition (cs.CV)	Minghui Liao, Zhaoyi Wan, Cong Yao, Kai Chen, Xiang Bai
1911.09074	Search to Distill: Pearls are Everywhere but not the Eyes	Computer Vision and Pattern Recognition (cs.CV)	Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, Xiaogang Wang
1911.09391	Accelerating Reinforcement Learning with Suboptimal Guidance	Machine Learning (cs.LG)	Eivind Bøhn, Signe Moe, Tor Arne Johansen
1911.09418	MSD: Multi-Self-Distillation Learning via Multi-classifiers within Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Yunteng Luan, Hanyu Zhao, Zhi Yang, Yafei Dai
1911.09450	Few Shot Network Compression via Cross Distillation	Machine Learning (cs.LG)	Haoli Bai, Jiaxiang Wu, Irwin King, Michael Lyu
1911.09464	Quantization Networks	Computer Vision and Pattern Recognition (cs.CV)	Jiwei Yang, Xu Shen, Jun Xing, Xinmei Tian, Houqiang Li, Bing Deng, Jianqiang Huang, Xiansheng Hua
1911.09817	Graph Pruning for Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Mingyang Zhang, Xinyi Yu, Jingtao Rong, Linlin Ou, Weidong Zhang
1911.09837	Graph Convolution Networks for Probabilistic Modeling of Driving Acceleration	Machine Learning (cs.LG)	Jianyu Su, Peter A. Beling, Rui Guo, Kyungtae Han
1911.09895	Visual Relationship Detection with Low Rank Non-Negative Tensor Decomposition	Computer Vision and Pattern Recognition (cs.CV)	Mohammed Haroon Dupty, Zhen Zhang, Wee Sun Lee
1911.10090	Learning End-To-End Scene Flow by Distilling Single Tasks Knowledge	Computer Vision and Pattern Recognition (cs.CV)	Filippo Aleotti, Matteo Poggi, Fabio Tosi, Stefano Mattoccia
1911.10321	Compressing Representations for Embedded Deep Learning	Machine Learning (cs.LG)	Juliano S. Assine, Alan Godoy, Eduardo Valle
1911.10434	Low Rank Approximation for Smoothing Spline via Eigensystem Truncation	Machine Learning (stat.ML)	Danqing Xu, Yuedong Wang
1911.10636	Pyramid Vector Quantization and Bit Level Sparsity in Weights for Efficient Neural Networks Inference	Computer Vision and Pattern Recognition (cs.CV)	Vincenzo Liguori
1911.10988	Sparsity through evolutionary pruning prevents neuronal networks from overfitting	Neural and Evolutionary Computing (cs.NE)	Richard C. Gerum, André Erpenbeck, Patrick Krauss, Achim Schilling
1911.11065	Knowledge Distillation in Document Retrieval	Information Retrieval (cs.IR)	Siamak Shakeri, Abhinav Sethy, Cheng Cheng
1911.11170	Real-Time Object Tracking via Meta-Learning: Efficient Model Adaptation and One-Shot Channel Pruning	Computer Vision and Pattern Recognition (cs.CV)	Ilchae Jung, Kihyun You, Hyeonwoo Noh, Minsu Cho, Bohyung Han
1911.11177	Structured Multi-Hashing for Model Compression	Machine Learning (cs.LG)	Elad Eban, Yair Movshovitz-Attias, Hao Wu, Mark Sandler, Andrew Poon, Yerlan Idelbayev, Miguel A. Carreira-Perpinan
1911.11502	Hearing Lips: Improving Lip Reading by Distilling Speech Recognizers	Computer Vision and Pattern Recognition (cs.CV)	Ya Zhao, Rui Xu, Xinchao Wang, Peng Hou, Haihong Tang, Mingli Song
1911.11554	Multi-source Distilling Domain Adaptation	Machine Learning (cs.LG)	Sicheng Zhao, Guangzhi Wang, Shanghang Zhang, Yang Gu, Yaxian Li, Zhichao Song, Pengfei Xu, Runbo Hu, Hua Chai, Kurt Keutzer
1911.12446	QubitHD: A Stochastic Acceleration Method for HD Computing-Based Machine Learning	Machine Learning (cs.LG)	Samuel Bosch, Alexander Sanchez de la Cerda, Mohsen Imani, Tajana Simunic Rosing, Giovanni De Micheli
1911.12491	QKD: Quantization-aware Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Jangho Kim, Yash Bhalgat, Jinwon Lee, Chirag Patel, Nojun Kwak
1911.12740	Data-Driven Compression of Convolutional Neural Networks	Machine Learning (cs.LG)	Ramit Pahwa, Manoj Ghuhan Arivazhagan, Ankur Garg, Siddarth Krishnamoorthy, Rohit Saxena, Sunav Choudhary
1911.12747	ASR is all you need: cross-modal distillation for lip reading	Computer Vision and Pattern Recognition (cs.CV)	Triantafyllos Afouras, Joon Son Chung, Andrew Zisserman
1911.12990	Semi-Relaxed Quantization with DropBits: Training Low-Bit Neural Networks via Bit-wise Regularization	Computer Vision and Pattern Recognition (cs.CV)	Jihun Yun, Jung Hyun Lee, Sung Ju Hwang, Eunho Yang
1911.13019	Towards Oracle Knowledge Distillation with Neural Architecture Search	Machine Learning (cs.LG)	Minsoo Kang, Jonghwan Mun, Bohyung Han
1911.13053	Blockwisely Supervised Neural Architecture Search with Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Changlin Li, Jiefeng Peng, Liuchun Yuan, Guangrun Wang, Xiaodan Liang, Liang Lin, Xiaojun Chang
1911.13056	Distributed Soft Actor-Critic with Multivariate Reward Representation and Knowledge Distillation	Artificial Intelligence (cs.AI)	Dmitry Akimov
1912.00120	One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation	Machine Learning (cs.LG)	Matthew Shunshi Zhang, Bradly Stadie
1912.00200	Pruning at a Glance: Global Neural Pruning for Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Abdullah Salama, Oleksiy Ostapenko, Tassilo Klein, Moin Nabi
1912.00350	Online Knowledge Distillation with Diverse Peers	Machine Learning (cs.LG)	Defang Chen, Jian-Ping Mei, Can Wang, Yan Feng, Chun Chen
1912.00583	Anomaly Detection in Particulate Matter Sensor using Hypothesis Pruning Generative Adversarial Network	Machine Learning (cs.LG)	YeongHyeon Park, Won Seok Park, Yeong Beom Kim, Seok Woong Chang
1912.00835	Low Rank Factorization for Compact Multi-Head Self-Attention	Computation and Language (cs.CL)	Sneha Mehta, Huzefa Rangwala, Naren Ramakrishnan
1912.01274	The Knowledge Within: Methods for Data-Free Model Compression	Machine Learning (cs.LG)	Matan Haroush, Itay Hubara, Elad Hoffer, Daniel Soudry
1912.02254	Deep Model Compression via Deep Reinforcement Learning	Machine Learning (cs.LG)	Huixin Zhan, Yongcan Cao
1912.02854	An Accelerated Correlation Filter Tracker	Computer Vision and Pattern Recognition (cs.CV)	Tianyang Xu, Zhen-Hua Feng, Xiao-Jun Wu, Josef Kittler
1912.02973	LaTeS: Latent Space Distillation for Teacher-Student Driving Policy Learning	Computer Vision and Pattern Recognition (cs.CV)	Albert Zhao, Tong He, Yitao Liang, Haibin Huang, Guy Van den Broeck, Stefano Soatto
1912.03145	Face Recognition via Locality Constrained Low Rank Representation and Dictionary Learning	Computer Vision and Pattern Recognition (cs.CV)	He-Feng Yin, Xiao-Jun Wu, Josef Kittler
1912.03334	Explaining Sequence-Level Knowledge Distillation as Data-Augmentation for Neural Machine Translation	Computation and Language (cs.CL)	Mitchell A. Gordon, Kevin Duh
1912.03433	Deep Generalization of Structured Low Rank Algorithms (Deep-SLR)	Machine Learning (cs.LG)	Aniket Pramanik, Hemant Aggarwal, Mathews Jacob
1912.03435	Tensor Low Rank Modeling and Its Applications in Signal Processing	Signal Processing (eess.SP)	Baburaj Madathil, Sameera V Mohd Sagheer, Abdu Rahiman V, Anju Jose Tom, Baiju P S, Jobin Francis, Sudhish N. George
1912.03647	Lossless Compression for 3DCNNs Based on Tensor Train Decomposition	Computer Vision and Pattern Recognition (cs.CV)	Dingheng Wang, Guangshe Zhao, Guoqi Li, Lei Deng, Yang Wu
1912.03734	Unified Signal Compression Using Generative Adversarial Networks	Signal Processing (eess.SP)	Bowen Liu, Ang Cao, Hun-seok Kim
1912.04050	PhoneBit: Efficient GPU-Accelerated Binary Neural Network Inference Engine for Mobile Phones	Distributed, Parallel, and Cluster Computing (cs.DC)	Gang Chen, Shengyu He, Haitao Meng, Kai Huang
1912.04548	Maximum Average Entropy-Based Quantization of Local Observations for Distributed Detection	Signal Processing (eess.SP)	Muath A. Wahdan, Mustafa A. Altınkaya
1912.04695	Transparent Classification with Multilayer Logical Perceptrons and Random Binarization	Machine Learning (cs.LG)	Zhuo Wang, Wei Zhang, Ning Liu, Jianyong Wang
1912.04822	libmolgrid: GPU Accelerated Molecular Gridding for Deep Learning Applications	Machine Learning (cs.LG)	Jocelyn Sunseri, David Ryan Koes
1912.04845	Magnitude and Uncertainty Pruning Criterion for Neural Networks	Machine Learning (cs.LG)	Vinnie Ko, Stefan Oehmcke, Fabian Gieseke
1912.05078	An Improving Framework of regularization for Network Compression	Machine Learning (cs.LG)	E Zhenqian, Gao Weiguo
1912.05304	Learning Agent Communication under Limited Bandwidth by Message Pruning	Artificial Intelligence (cs.AI)	Hangyu Mao, Zhengchao Zhang, Zhen Xiao, Zhibo Gong, Yan Ni
1912.05524	GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences	Computer Vision and Pattern Recognition (cs.CV)	Prune Truong, Martin Danelljan, Radu Timofte
1912.05831	STEERAGE: Synthesis of Neural Networks Using Architecture Search and Grow-and-Prune Methods	Neural and Evolutionary Computing (cs.NE)	Shayan Hassantabar, Xiaoliang Dai, Niraj K. Jha
1912.06638	WaLDORf: Wasteless Language-model Distillation On Reading-comprehension	Machine Learning (cs.LG)	James Yi Tian, Alexander P. Kreuzer, Pai-Hung Chen, Hans-Martin Will
1912.07106	Towards Building a Real Time Mobile Device Bird Counting System Through Synthetic Data Training and Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Runde Yang
1912.07768	Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data	Machine Learning (cs.LG)	Felipe Petroski Such, Aditya Rawal, Joel Lehman, Kenneth O. Stanley, Jeff Clune
1912.07806	Joint Architecture and Knowledge Distillation in Convolutional Neural Network for Offline Handwritten Chinese Text Recognition	Computer Vision and Pattern Recognition (cs.CV)	Zi-Rui Wang, Jun Du
1912.07863	In Defense of the Triplet Loss Again: Learning Robust Person Re-Identification with Fast Approximated Triplet Loss and Label Distillation	Computer Vision and Pattern Recognition (cs.CV)	Ye Yuan, Wuyang Chen, Yang Yang, Zhangyang Wang
1912.08422	Distilling Structured Knowledge into Embeddings for Explainable and Accurate Recommendation	Information Retrieval (cs.IR)	Yuan Zhang, Xiaoran Xu, Hanning Zhou, Yan Zhang
1912.08756	Interleaved Composite Quantization for High-Dimensional Similarity Search	Machine Learning (cs.LG)	Soroosh Khoram, Stephen J Wright, Jing Li
1912.08792	TOCO: A Framework for Compressing Neural Network Models Based on Tolerance Analysis	Machine Learning (cs.LG)	Soroosh Khoram, Jing Li
1912.08795	Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion	Machine Learning (cs.LG)	Hongxu Yin, Pavlo Molchanov, Zhizhong Li, Jose M. Alvarez, Arun Mallya, Derek Hoiem, Niraj K. Jha, Jan Kautz
1912.08881	Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning	Machine Learning (cs.LG)	Seul-Ki Yeom, Philipp Seegerer, Sebastian Lapuschkin, Simon Wiedemann, Klaus-Robert Müller, Wojciech Samek
1912.08883	Adaptive Loss-aware Quantization for Multi-bit Networks	Computer Vision and Pattern Recognition (cs.CV)	Zhongnan Qu, Zimu Zhou, Yun Cheng, Lothar Thiele
1912.09091	Overcoming Long-term Catastrophic Forgetting through Adversarial Neural Pruning and Synaptic Consolidation	Machine Learning (cs.LG)	Jian Peng Bo Tang, Hao Jiang, Zhuo Li, Yinjie Lei, Tao Lin, Haifeng Li
1912.09236	Neural Networks Weights Quantization: Target None-retraining Ternary (TNT)	Machine Learning (cs.LG)	Tianyu Zhang, Lei Zhu, Qian Zhao, Kilho Shin
1912.09666	AdaBits: Neural Network Quantization with Adaptive Bit-Widths	Computer Vision and Pattern Recognition (cs.CV)	Qing Jin, Linjie Yang, Zhenyu Liao
1912.09802	Taxonomy and Evaluation of Structured Compression of Convolutional Neural Networks	Machine Learning (cs.LG)	Andrey Kuzmin, Markus Nagel, Saurabh Pitre, Sandeep Pendyam, Tijmen Blankevoort, Max Welling
1912.10087	EAST: Encoding-Aware Sparse Training for Deep Memory Compression of ConvNets	Machine Learning (cs.LG)	Matteo Grimaldi, Valentino Peluso, Andrea Calimera
1912.10178	DBP: Discrimination Based Block-Level Pruning for Deep Model Acceleration	Computer Vision and Pattern Recognition (cs.CV)	Wenxiao Wang, Shuai Zhao, Minghao Chen, Jinming Hu, Deng Cai, Haifeng Liu
1912.10207	Towards Efficient Training for Neural Network Quantization	Computer Vision and Pattern Recognition (cs.CV)	Qing Jin, Linjie Yang, Zhenyu Liao
1912.10850	The State of Knowledge Distillation for Classification	Machine Learning (cs.LG)	Fabian Ruffy, Karanbir Chahal
1912.10982	DMCL: Distillation Multiple Choice Learning for Multimodal Action Recognition	Computer Vision and Pattern Recognition (cs.CV)	Nuno C. Garcia, Sarah Adel Bargal, Vitaly Ablavsky, Pietro Morerio, Vittorio Murino, Stan Sclaroff
1912.11006	Data-Free Adversarial Distillation	Machine Learning (cs.LG)	Gongfan Fang, Jie Song, Chengchao Shen, Xinchao Wang, Da Chen, Mingli Song
1912.11527	Pruning Deep Neural Networks Architectures with Evolution Strategy	Neural and Evolutionary Computing (cs.NE)	Francisco Erivaldo Fernandes Junior, Gary G. Yen
1912.11554	Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro	Machine Learning (stat.ML)	Du Phan, Neeraj Pradhan, Martin Jankowiak
1912.11853	Domain Adaptation Regularization for Spectral Pruning	Computer Vision and Pattern Recognition (cs.CV)	Laurent Dillard, Yosuke Shinya, Taiji Suzuki
1912.12630	Real-time Policy Distillation in Deep Reinforcement Learning	Machine Learning (cs.LG)	Yuxiang Sun, Pooyan Fazli
1912.12953	RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing	Distributed, Parallel, and Cluster Computing (cs.DC)	Liu Ke, Udit Gupta, Carole-Jean Wu, Benjamin Youngjae Cho, Mark Hempstead, Brandon Reagen, Xuan Zhang, David Brooks, Vikas Chandra, Utku Diril, Amin Firoozshahian, Kim Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Meng Li, Bert Maher, Dheevatsa Mudigere, Maxim Naumov, Martin Schatz, Mikhail Smelyanskiy, Xiaodong Wang
1912.13179	Modeling Teacher-Student Techniques in Deep Neural Networks for Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Sajjad Abbasi, Mohsen Hajabdollahi, Nader Karimi, Shadrokh Samavi
2001.00138	PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning	Machine Learning (cs.LG)	Wei Niu, Xiaolong Ma, Sheng Lin, Shihao Wang, Xuehai Qian, Xue Lin, Yanzhi Wang, Bin Ren
2001.00218	Lossless Compression of Deep Neural Networks	Machine Learning (cs.LG)	Thiago Serra, Abhinav Kumar, Srikumar Ramalingam
2001.00281	ZeroQ: A Novel Zero Shot Quantization Framework	Computer Vision and Pattern Recognition (cs.CV)	Yaohui Cai, Zhewei Yao, Zhen Dong, Amir Gholami, Michael W. Mahoney, Kurt Keutzer
2001.00503	Joint Goal and Strategy Inference across Heterogeneous Demonstrators via Reward Network Distillation	Machine Learning (cs.LG)	Letian Chen, Rohan Paleja, Muyleng Ghuy, Matthew Gombolay
2001.00602	Accelerating Smooth Games by Manipulating Spectral Shapes	Machine Learning (cs.LG)	Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
2001.01050	Discrimination-aware Network Pruning for Deep Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Jing Liu, Bohan Zhuang, Zhuangwei Zhuang, Yong Guo, Junzhou Huang, Jinhui Zhu, Mingkui Tan
2001.01536	Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification	Computer Vision and Pattern Recognition (cs.CV)	Liuyu Xiang, Guiguang Ding
2001.01755	Investigation and Analysis of Hyper and Hypo neuron pruning to selectively update neurons during Unsupervised Adaptation	Machine Learning (cs.LG)	Vikramjit Mitra, Horacio Franco
2001.01797	Bridge Modal Identification using Acceleration Measurements within Moving Vehicles	Signal Processing (eess.SP)	Soheil Sadeghi Eshkevari, Thomas J. Matarazzo, Shamim N. Pakzad
2001.01842	Single-bit Quantization Capacity of Binary-input Continuous-output Channels	Signal Processing (eess.SP)	Thuan Nguyen, Thinh Nguyen
2001.02786	Least squares binary quantization of neural networks	Machine Learning (cs.LG)	Hadi Pouransari, Zhucheng Tu, Oncel Tuzel
2001.02935	Multipass SAR Interferometry Based on Total Variation Regularized Robust Low Rank Tensor Decomposition	Signal Processing (eess.SP)	Jian Kang, Yuanyuan Wang, Xiao Xiang Zhu
2001.03102	Compression of convolutional neural networks for high performance imagematching tasks on mobile devices	Computer Vision and Pattern Recognition (cs.CV)	Roy Miles, Krystian Mikolajczyk
2001.03111	Unpaired Multi-modal Segmentation via Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Qi Dou, Quande Liu, Pheng Ann Heng, Ben Glocker
2001.03199	Downlink Fronthaul Compression in Frequency Domain using OpenAirInterface	Signal Processing (eess.SP)	Cleverson Nahum, Leonardo Ramalho, Joary Fortuna, Chenguang Lu, Miguel Berg, Igor Almeida, Aldebaro Klautau
2001.03311	Guess First to Enable Better Compression and Adversarial Robustness	Machine Learning (cs.LG)	Sicheng Zhu, Bang An, Shiyu Niu
2001.03554	Pruning Convolutional Neural Networks with Self-Supervision	Computer Vision and Pattern Recognition (cs.CV)	Mathilde Caron, Ari Morcos, Piotr Bojanowski, Julien Mairal, Armand Joulin
2001.03569	Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analytics	Computer Vision and Pattern Recognition (cs.CV)	Ling-Yu Duan, Jiaying Liu, Wenhan Yang, Tiejun Huang, Wen Gao
2001.03851	Deep Optimized Multiple Description Image Coding via Scalar Quantization Learning	Computer Vision and Pattern Recognition (cs.CV)	Lijun Zhao, Huihui Bai, Anhong Wang, Yao Zhao
2001.03955	Aggregated Learning: A Vector-Quantization Approach to Learning Neural Network Classifiers	Machine Learning (cs.LG)	Masoumeh Soflaei, Hongyu Guo, Ali Al-Bashabsheh, Yongyi Mao, Richong Zhang
2001.04062	Modeling of Pruning Techniques for Deep Neural Networks Simplification	Computer Vision and Pattern Recognition (cs.CV)	Morteza Mousa Pasandi, Mohsen Hajabdollahi, Nader Karimi, Shadrokh Samavi
2001.04246	AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search	Computation and Language (cs.CL)	Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li, Bolin Ding, Hongbo Deng, Jun Huang, Wei Lin, Jingren Zhou
2001.04625	Asymmetric Correlation Quantization Hashing for Cross-modal Retrieval	Information Retrieval (cs.IR)	Lu Wang, Jie Yang
2001.04694	Hydra: Preserving Ensemble Diversity for Model Distillation	Machine Learning (cs.LG)	Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton
2001.04850	Quantisation and Pruning for Neural Network Compression and Regularisation	Machine Learning (cs.LG)	Kimessha Paupamah, Steven James, Richard Klein
2001.05012	PoPS: Policy Pruning and Shrinking for Deep Reinforcement Learning	Machine Learning (cs.LG)	Dor Livne, Kobi Cohen
2001.05050	On Iterative Neural Network Pruning, Reinitialization, and the Similarity of Masks	Machine Learning (cs.LG)	Michela Paganini, Jessica Forde
2001.05197	Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification	Computer Vision and Pattern Recognition (cs.CV)	Xin Jin, Cuiling Lan, Wenjun Zeng, Zhibo Chen
2001.05314	Embedding Compression with Isotropic Iterative Quantization	Computation and Language (cs.CL)	Siyu Liao, Jie Chen, Yanzhi Wang, Qinru Qiu, Bo Yuan
2001.05545	A "Network Pruning Network" Approach to Deep Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri, Piyush Rai
2001.06139	FRaZ: A Generic High-Fidelity Fixed-Ratio Lossy Compression Framework for Scientific Floating-point Data	Distributed, Parallel, and Cluster Computing (cs.DC)	Robert Underwood, Sheng Di, Jon C. Calhoun, Franck Cappello
2001.06472	Gradient descent with momentum --- to accelerate or to super-accelerate?	Machine Learning (cs.LG)	Goran Nakerst, John Brennan, Masudul Haque
2001.06590	A Foreground-background Parallel Compression with Residual Encoding for Surveillance Video	Computer Vision and Pattern Recognition (cs.CV)	Lirong Wu, Kejie Huang, Haibin Shen, Lianli Gao
2001.06613	Accelerating the Registration of Image Sequences by Spatio-temporal Multilevel Strategies	Signal Processing (eess.SP)	Hari Om Aggrawal, Jan Modersitzki
2001.07809	Depth-Based Selective Blurring in Stereo Images Using Accelerated Framework	Computer Vision and Pattern Recognition (cs.CV)	Subhayan Mukherjee, Ram Mohana Reddy Guddeti
2001.08055	Up to two billion times acceleration of scientific simulations with deep neural architecture search	Machine Learning (stat.ML)	M. F. Kasim, D. Watson-Parris, L. Deaconu, S. Oliver, P. Hatfield, D. H. Froula, G. Gregori, M. Jarvis, S. Khatiwala, J. Korenaga, J. Topp-Mugglestone, E. Viezzer, S. M. Vinko
2001.08142	Pruning CNN's with linear filter ensembles	Machine Learning (cs.LG)	Csanád Sándor, Szabolcs Pável, Lehel Csató
2001.08357	BLK-REW: A Unified Block-based DNN Pruning Framework using Reweighted Regularization Method	Machine Learning (cs.LG)	Xiaolong Ma, Zhengang Li, Yifan Gong, Tianyun Zhang, Wei Niu, Zheng Zhan, Pu Zhao, Jian Tang, Xue Lin, Bin Ren, Yanzhi Wang
2001.08514	Filter Sketch for Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Mingbao Lin, Rongrong Ji, Shaojie Li, Qixiang Ye, Yonghong Tian, Jianzhuang Liu, Qi Tian
2001.08565	Channel Pruning via Automatic Structure Search	Computer Vision and Pattern Recognition (cs.CV)	Mingbao Lin, Rongrong Ji, Yuxin Zhang, Baochang Zhang, Yongjian Wu, Yonghong Tian
2001.08650	Structured Compression and Sharing of Representational Space for Continual Learning	Machine Learning (cs.LG)	Gobinda Saha, Isha Garg, Aayush Ankit, Kaushik Roy
2001.08839	SS-Auto: A Single-Shot, Automatic Structured Weight Pruning Framework of DNNs with Ultra-High Efficiency	Machine Learning (cs.LG)	Zhengang Li, Yifan Gong, Xiaolong Ma, Sijia Liu, Mengshu Sun, Zheng Zhan, Zhenglun Kong, Geng Yuan, Yanzhi Wang
2001.08878	Progressive Local Filter Pruning for Image Retrieval Acceleration	Computer Vision and Pattern Recognition (cs.CV)	Xiaodong Wang, Zhedong Zheng, Yang He, Fei Yan, Zhiqiang Zeng, Yi Yang
2001.08896	Compressing Language Models using Doped Kronecker Products	Machine Learning (cs.LG)	Urmish Thakker, Paul Whatmough, Matthew Mattina, Jesse Beu
2001.08950	PoWER-BERT: Accelerating BERT inference for Classification Tasks	Machine Learning (cs.LG)	Saurabh Goyal, Anamitra Roy Choudhary, Venkatesan Chakaravarthy, Saurabh ManishRaje, Yogish Sabharwal, Ashish Verma
2001.09595	Developing Multi-Task Recommendations with Long-Term Rewards via Policy Distilled Reinforcement Learning	Machine Learning (cs.LG)	Xi Liu, Li Li, Ping-Chun Hsieh, Muhe Xie, Yong Ge, Rui Chen
2001.09882	Efficient and Stable Graph Scattering Transforms via Pruning	Signal Processing (eess.SP)	Vassilis N. Ioannidis, Siheng Chen, Georgios B. Giannakis
2001.10318	Margin Maximization as Lossless Maximal Compression	Machine Learning (cs.LG)	Nikolaos Nikolaou, Henry Reeve, Gavin Brown
2001.11235	Learning Discrete Distributions by Dequantization	Machine Learning (cs.LG)	Emiel Hoogeboom, Taco S. Cohen, Jakub M. Tomczak
2001.11612	Search for Better Students to Learn Distilled Knowledge	Computer Vision and Pattern Recognition (cs.CV)	Jindong Gu, Volker Tresp
2002.00104	Post-Training Piecewise Linear Quantization for Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Jun Fang, Ali Shafiee, Hamzah Abdel-Aziz, David Thorsley, Georgios Georgiadis, Joseph Hassoun
2002.00149	Periodic Intra-Ensemble Knowledge Distillation for Reinforcement Learning	Machine Learning (cs.LG)	Zhang-Wei Hong, Prabhat Nagarajan, Guilherme Maeda
2002.00497	Accelerating Cooperative Planning for Automated Vehicles with Learned Heuristics and Monte Carlo Tree Search	Machine Learning (cs.LG)	Karl Kurzer, Marcus Fechner, J. Marius Zöllner
2002.00523	Automatic Pruning for Quantized Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Luis Guerra, Bohan Zhuang, Ian Reid, Tom Drummond
2002.00552	DWM: A Decomposable Winograd Method for Convolution Acceleration	Machine Learning (cs.LG)	Di Huang, Xishan Zhang, Rui Zhang, Tian Zhi, Deyuan He, Jiaming Guo, Chang Liu, Qi Guo, Zidong Du, Shaoli Liu, Tianshi Chen, Yunji Chen
2002.00585	Proving the Lottery Ticket Hypothesis: Pruning is All You Need	Machine Learning (cs.LG)	Eran Malach, Gilad Yehudai, Shai Shalev-Shwartz, Ohad Shamir
2002.00733	Generation-Distillation for Efficient Natural Language Understanding in Low-Data Settings	Computation and Language (cs.CL)	Luke Melas-Kyriazi, George Han, Celine Liang
2002.01337	Cooperative Learning via Federated Distillation over Fading Channels	Signal Processing (eess.SP)	Jin-Hyun Ahn, Osvaldo Simeone, Joonhyuk Kang
2002.01547	Accelerating Psychometric Screening Tests With Bayesian Active Differential Selection	Machine Learning (cs.LG)	Trevor J. Larsen, Gustavo Malkomes, Dennis L. Barbour
2002.01769	Robust Clock Synchronization via Low Rank Approximation in Wireless Networks	Signal Processing (eess.SP)	Osama Elnahas, Zhi Quan
2002.01775	Feature-map-level Online Adversarial Knowledge Distillation	Machine Learning (cs.LG)	Inseop Chung, SeongUk Park, Jangho Kim, Nojun Kwak
2002.02202	Transfer Heterogeneous Knowledge Among Peer-to-Peer Teammates: A Model Distillation Approach	Artificial Intelligence (cs.AI)	Zeyue Xue, Shuang Luo, Chao Wu, Pan Zhou, Kaigui Bian, Wei Du
2002.02547	Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow	Machine Learning (cs.LG)	Didrik Nielsen, Ole Winther
2002.02645	Accelerating Deep Learning Inference via Freezing	Machine Learning (cs.LG)	Adarsh Kumar, Arjun Balasubramanian, Shivaram Venkataraman, Aditya Akella
2002.02697	Accelerating Reinforcement Learning for Reaching using Continuous Curriculum Learning	Artificial Intelligence (cs.AI)	Sha Luo, Hamidreza Kasaei, Lambert Schomaker
2002.02842	Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification	Machine Learning (cs.LG)	Meet P. Vadera, Satya Narayan Shukla, Brian Jalaian, Benjamin M. Marlin
2002.02925	BERT-of-Theseus: Compressing BERT by Progressive Module Replacing	Computation and Language (cs.CL)	Canwen Xu, Wangchunshu Zhou, Tao Ge, Furu Wei, Ming Zhou
2002.02949	Activation Density driven Energy-Efficient Pruning in Training	Machine Learning (cs.LG)	Timothy Foldy-Porto, Priyadarshini Panda
2002.02998	Improving the Adversarial Robustness of Transfer Learning via Noisy Feature Distillation	Machine Learning (cs.LG)	Ting-Wu Chin, Cha Zhang, Diana Marculescu
2002.03090	BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization	Machine Learning (cs.LG)	Miloš Nikolić, Ghouthi Boukli Hacene, Ciaran Bannon, Alberto Delmas Lascorz, Matthieu Courbariaux, Yoshua Bengio, Vincent Gripon, Andreas Moshovos
2002.03299	Convolutional Neural Network Pruning Using Filter Attenuation	Computer Vision and Pattern Recognition (cs.CV)	Morteza Mousa-Pasandi, Mohsen Hajabdollahi, Nader Karimi, Shadrokh Samavi, Shahram Shirani
2002.03532	Understanding and Improving Knowledge Distillation	Machine Learning (cs.LG)	Jiaxi Tang, Rakesh Shivanna, Zhe Zhao, Dong Lin, Anima Singh, Ed H. Chi, Sagar Jain
2002.03577	Accelerating RNN Transducer Inference via One-Step Constrained Beam Search	Machine Learning (cs.LG)	Juntae Kim, Yoonhan Lee
2002.03627	End-to-End Facial Deep Learning Feature Compression with Teacher-Student Enhancement	Computer Vision and Pattern Recognition (cs.CV)	Shurun Wang, Wenhan Yang, Shiqi Wang
2002.03662	Distribution Distillation Loss: Generic Approach for Improving Face Recognition from Hard Samples	Computer Vision and Pattern Recognition (cs.CV)	Yuge Huang, Pengcheng Shen, Ying Tai, Shaoxin Li, Xiaoming Liu, Jilin Li, Feiyue Huang, Rongrong Ji
2002.03742	Dynamic Error-bounded Lossy Compression (EBLC) to Reduce the Bandwidth Requirement for Real-time Vision-based Pedestrian Safety Applications	Computer Vision and Pattern Recognition (cs.CV)	Mizanur Rahman, Mhafuzul Islam, Jon C. Calhoun, Mashrur Chowdhury
2002.03875	Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration	Machine Learning (stat.ML)	Bindya Venkatesh, Jayaraman J. Thiagarajan, Kowshik Thopalli, Prasanna Sattigeri
2002.03936	Subclass Distillation	Machine Learning (cs.LG)	Rafael Müller, Simon Kornblith, Geoffrey Hinton
2002.04809	Lookahead: A Far-Sighted Alternative of Magnitude-based Pruning	Machine Learning (cs.LG)	Sejun Park, Jaeho Lee, Sangwoo Mo, Jinwoo Shin
2002.05604	Efficient And Scalable Neural Residual Waveform Coding With Collaborative Quantization	Audio and Speech Processing (eess.AS)	Kai Zhen, Mi Suk Lee, Jongmo Sung, Seungkwon Beack, Minje Kim
2002.05715	Self-Distillation Amplifies Regularization in Hilbert Space	Machine Learning (cs.LG)	Hossein Mobahi, Mehrdad Farajtabar, Peter L. Bartlett
2002.06048	Layer-wise Pruning and Auto-tuning of Layer-wise Learning Rates in Fine-tuning of Deep Networks	Computer Vision and Pattern Recognition (cs.CV)	Youngmin Ro, Jin Young Choi
2002.06275	TwinBERT: Distilling Knowledge to Twin-Structured BERT Models for Efficient Retrieval	Information Retrieval (cs.IR)	Wenhao Lu, Jian Jiao, Ruofei Zhang
2002.07036	Back-and-Forth prediction for deep tensor compression	Machine Learning (cs.LG)	Hyomin Choi, Robert A. Cohen, Ivan V. Bajic
2002.07051	Retrain or not retrain? -- efficient pruning methods of deep CNN networks	Machine Learning (cs.LG)	Marcin Pietron, Maciej Wielgosz
2002.07215	STANNIS: Low-Power Acceleration of Deep Neural Network Training Using Computational Storage	Distributed, Parallel, and Cluster Computing (cs.DC)	Ali HeydariGorji, Mahdi Torabzadehkashi, Siavash Rezaei, Hossein Bobarshad, Vladimir Alves, Pai H. Chou
2002.07418	KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge	Artificial Intelligence (cs.AI)	Peng Zhang, Jianye Hao, Weixun Wang, Hongyao Tang, Yi Ma, Yihai Duan, Yan Zheng
2002.07520	Gradient $\ell_1$ Regularization for Quantization Robustness	Machine Learning (cs.LG)	Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling
2002.07686	Robust Quantization: One Model to Rule Them All	Machine Learning (cs.LG)	Moran Shkolnik, Brian Chmiel, Ron Banner, Gil Shomron, Yuri Nahshan, Alex Bronstein, Uri Weiser
2002.08204	SYMOG: learning symmetric mixture of Gaussian modes for improved fixed-point quantization	Machine Learning (cs.LG)	Lukas Enderich, Fabian Timm, Wolfram Burgard
2002.08258	Knapsack Pruning with Inner Distillation	Machine Learning (cs.LG)	Yonathan Aflalo, Asaf Noy, Ming Lin, Itamar Friedman, Lihi Zelnik
2002.08307	Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning	Computation and Language (cs.CL)	Mitchell A. Gordon, Kevin Duh, Nicholas Andrews
2002.08326	Balancing Efficiency and Flexibility for DNN Acceleration via Temporal GPU-Systolic Array Integration	Distributed, Parallel, and Cluster Computing (cs.DC)	Cong Guo, Yangjie Zhou, Jingwen Leng, Yuhao Zhu, Zidong Du, Quan Chen, Chao Li, Minyi Guo, Bin Yao
2002.08679	Neural Network Compression Framework for fast model inference	Computer Vision and Pattern Recognition (cs.CV)	Alexander Kozlov, Ivan Lazarevich, Vasily Shamporov, Nikolay Lyalyushkin, Yury Gorbachev
2002.08697	Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs	Machine Learning (cs.LG)	Valentin Radu, Kuba Kaszyk, Yuan Wen, Jack Turner, Jose Cano, Elliot J. Crowley, Bjorn Franke, Amos Storkey, Michael O'Boyle
2002.08797	Pruning untrained neural networks: Principles and Analysis	Machine Learning (stat.ML)	Soufiane Hayou, Jean-Francois Ton, Arnaud Doucet, Yee Whye Teh
2002.09049	Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision	Machine Learning (cs.LG)	Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu
2002.09077	Accelerating Reinforcement Learning with a Directional-Gaussian-Smoothing Evolution Strategy	Machine Learning (cs.LG)	Jiaxing Zhang, Hoang Tran, Guannan Zhang
2002.09168	Residual Knowledge Distillation	Machine Learning (cs.LG)	Mengya Gao, Yujun Shen, Quanquan Li, Chen Change Loy
2002.09607	Multi-Representation Knowledge Distillation For Audio Classification	Multimedia (cs.MM)	Liang Gao, Kele Xu, Huaimin Wang, Yuxing Peng
2002.09958	Gradual Channel Pruning while Training using Feature Relevance Scores for Convolutional Neural Networks	Machine Learning (cs.LG)	Sai Aparna Aketi, Sourjya Roy, Anand Raghunathan, Kaushik Roy
2002.10179	HRank: Filter Pruning using High-Rank Feature Map	Computer Vision and Pattern Recognition (cs.CV)	Mingbao Lin, Rongrong Ji, Yan Wang, Yichen Zhang, Baochang Zhang, Yonghong Tian, Ling Shao
2002.10345	Improving BERT Fine-Tuning via Self-Ensemble and Self-Distillation	Computation and Language (cs.CL)	Yige Xu, Xipeng Qiu, Ligao Zhou, Xuanjing Huang
2002.10509	On Pruning Adversarially Robust Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana
2002.10583	Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent	Machine Learning (cs.LG)	Bao Wang, Tan M. Nguyen, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
2002.10621	Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements	Machine Learning (cs.LG)	Alberto Dalla Libera, Diego Romeres, Devesh K. Jha, Bill Yerazunis, Daniel Nikovski
2002.10636	Non-Volatile Memory Array Based Quantization- and Noise-Resilient LSTM Neural Networks	Neural and Evolutionary Computing (cs.NE)	Wen Ma, Pi-Feng Chiu, Won Ho Choi, Minghai Qin, Daniel Bedau, Martin Lueker-Boden
2002.10941	A$^3$: Accelerating Attention Mechanisms in Neural Networks with Approximation	Distributed, Parallel, and Cluster Computing (cs.DC)	Tae Jun Ham, Sung Jun Jung, Seonghak Kim, Young H. Oh, Yeonhong Park, Yoonho Song, Jung-Hun Park, Sanghee Lee, Kyoung Park, Jae W. Lee, Deog-Kyoon Jeong
2002.10957	MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers	Computation and Language (cs.CL)	Wenhui Wang, Furu Wei, Li Dong, Hangbo Bao, Nan Yang, Ming Zhou
2002.11082	Optimal Gradient Quantization Condition for Communication-Efficient Distributed Training	Machine Learning (cs.LG)	An Xu, Zhouyuan Huo, Heng Huang
2002.11281	Generalized Product Quantization Network for Semi-supervised Image Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Young Kyun Jang, Nam Ik Cho
2002.11374	Adversarial Attack on Deep Product Quantization Network for Image Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Yan Feng, Bin Chen, Tao Dai, Shutao Xia
2002.11531	A general framework for ensemble distribution distillation	Machine Learning (stat.ML)	Jakob Lindqvist, Amanda Olmin, Fredrik Lindsten, Lennart Svensson
2002.11665	Profile Entropy: A Fundamental Measure for the Learnability and Compressibility of Discrete Distributions	Machine Learning (stat.ML)	Yi Hao, Alon Orlitsky
2002.11794	Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers	Computation and Language (cs.CL)	Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joseph E. Gonzalez
2002.11903	Acceleration of Actor-Critic Deep Reinforcement Learning for Visual Grasping in Clutter by State Representation Learning Based on Disentanglement of a Raw Input Image	Machine Learning (cs.LG)	Taewon Kim, Yeseong Park, Youngbin Park, Il Hong Suh
2002.11985	Compressing Large-Scale Transformer-Based Models: A Case Study on BERT	Machine Learning (cs.LG)	Prakhar Ganesh, Yao Chen, Xin Lou, Mohammad Ali Khan, Yin Yang, Deming Chen, Marianne Winslett, Hassan Sajjad, Preslav Nakov
2002.12410	On Biased Compression for Distributed Learning	Machine Learning (cs.LG)	Aleksandr Beznosikov, Samuel Horváth, Peter Richtárik, Mher Safaryan
2002.12414	On the Convergence of Nesterov's Accelerated Gradient Method in Stochastic Settings	Machine Learning (cs.LG)	Mahmoud Assran, Michael Rabbat
2002.12585	Exploring and Distilling Cross-Modal Information for Image Captioning	Computer Vision and Pattern Recognition (cs.CV)	Fenglin Liu, Xuancheng Ren, Yuanxin Liu, Kai Lei, Xu Sun
2002.12597	An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation	Machine Learning (cs.LG)	Makoto Takamoto, Yusuke Morishita, Hitoshi Imaoka
2002.12620	TextBrewer: An Open-Source Knowledge Distillation Toolkit for Natural Language Processing	Computation and Language (cs.CL)	Ziqing Yang, Yiming Cui, Zhipeng Chen, Wanxiang Che, Ting Liu, Shijin Wang, Guoping Hu
2002.12663	HOTCAKE: Higher Order Tucker Articulated Kernels for Deeper CNN Compression	Machine Learning (cs.LG)	Rui Lin, Ching-Yun Ko, Zhuolun He, Cong Chen, Yuan Cheng, Hao Yu, Graziano Chesi, Ngai Wong
2003.00058	Generalized Rational Variable Projection With Application in ECG Compression	Signal Processing (eess.SP)	Péter Kovács, Sándor Fridli, Ferenc Schipp
2003.00075	Learned Threshold Pruning	Machine Learning (cs.LG)	Kambiz Azarian, Yash Bhalgat, Jinwon Lee, Tijmen Blankevoort
2003.00146	Gradient-Based Deep Quantization of Neural Networks through Sinusoidal Adaptive Regularization	Machine Learning (cs.LG)	Ahmed T. Elthakeb, Prannoy Pilligundla, Fatemehsadat Mireshghallah, Tarek Elgindi, Charles-Alban Deledalle, Hadi Esmaeilzadeh
2003.00608	MBGD-RDA Training and Rule Pruning for Concise TSK Fuzzy Regression Models	Machine Learning (cs.LG)	Dongrui Wu
2003.00631	Sparsity Meets Robustness: Channel Pruning for the Feynman-Kac Formalism Principled Robust Deep Neural Nets	Machine Learning (cs.LG)	Thu Dinh, Bao Wang, Andrea L. Bertozzi, Stanley J. Osher
2003.00706	GPU-Accelerated Mobile Multi-view Style Transfer	Computer Vision and Pattern Recognition (cs.CV)	Puneet Kohli, Saravana Gunaseelan, Jason Orozco, Yiwen Hua, Edward Li, Nicolas Dahlquist
2003.00739	Long Short-Term Sample Distillation	Computer Vision and Pattern Recognition (cs.CV)	Liang Jiang, Zujie Wen, Zhongping Liang, Yafang Wang, Gerard de Melo, Zhe Li, Liangzhuang Ma, Jiaxing Zhang, Xiaolong Li, Yuan Qi
2003.01474	Distilled Hierarchical Neural Ensembles with Adaptive Inference Cost	Computer Vision and Pattern Recognition (cs.CV)	Adria Ruiz, Jakob Verbeek
2003.01794	Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection	Machine Learning (cs.LG)	Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam Klivans, Qiang Liu
2003.01836	A GPU-Accelerated Barycentric Lagrange Treecode	Distributed, Parallel, and Cluster Computing (cs.DC)	Nathan Vaughn, Leighton Wilson, Robert Krasny
2003.01876	Privacy-preserving Learning via Deep Net Pruning	Machine Learning (cs.LG)	Yangsibo Huang, Yushan Su, Sachin Ravi, Zhao Song, Sanjeev Arora, Kai Li
2003.02389	Comparing Rewinding and Fine-tuning in Neural Network Pruning	Machine Learning (cs.LG)	Alex Renda, Jonathan Frankle, Michael Carbin
2003.02449	Cluster Pruning: An Efficient Filter Pruning Method for Edge AI Vision Applications	Computer Vision and Pattern Recognition (cs.CV)	Chinthaka Gamanayake, Lahiru Jayasinghe, Benny Ng, Chau Yuen
2003.02586	MarginDistillation: distillation for margin-based softmax	Computer Vision and Pattern Recognition (cs.CV)	David Svitov, Sergey Alyamkin
2003.02628	Phoenix: A Low-Precision Floating-Point Quantization Oriented Architecture for Convolutional Neural Networks	Signal Processing (eess.SP)	Chen Wu, Mingyu Wang, Xiayu Li, Jicheng Lu, Kun Wang, Lei He
2003.02800	Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks	Machine Learning (cs.LG)	Sourjya Roy, Priyadarshini Panda, Gopalakrishnan Srinivasan, Anand Raghunathan
2003.02874	Optimizing JPEG Quantization for Classification Networks	Computer Vision and Pattern Recognition (cs.CV)	Zhijing Li, Christopher De Sa, Adrian Sampson
2003.02877	Distill, Adapt, Distill: Training Small, In-Domain Models for Neural Machine Translation	Computation and Language (cs.CL)	Mitchell A. Gordon, Kevin Duh
2003.03033	What is the State of Neural Network Pruning?	Machine Learning (cs.LG)	Davis Blalock, Jose Javier Gonzalez Ortiz, Jonathan Frankle, John Guttag
2003.03131	Morfessor EM+Prune: Improved Subword Segmentation with Expectation Maximization and Pruning	Computation and Language (cs.CL)	Stig-Arne Grönroos, Sami Virpioja, Mikko Kurimo
2003.03519	Distilling portable Generative Adversarial Networks for Image Translation	Computer Vision and Pattern Recognition (cs.CV)	Hanting Chen, Yunhe Wang, Han Shu, Changyuan Wen, Chunjing Xu, Boxin Shi, Chao Xu, Chang Xu
2003.03564	Ternary Compression for Communication-Efficient Federated Learning	Machine Learning (cs.LG)	Jinjin Xu, Wenli Du, Ran Cheng, Wangli He, Yaochu Jin
2003.03581	StyleGAN2 Distillation for Feed-forward Image Manipulation	Computer Vision and Pattern Recognition (cs.CV)	Yuri Viazovetskyi, Vladimir Ivashkin, Evgeny Kashin
2003.03603	Generative Low-bitwidth Data Free Quantization	Computer Vision and Pattern Recognition (cs.CV)	Shoukai Xu, Haokun Li, Bohan Zhuang, Jing Liu, Jiezhang Cao, Chuangrun Liang, Mingkui Tan
2003.03622	Explaining Knowledge Distillation by Quantifying the Knowledge	Machine Learning (cs.LG)	Xu Cheng, Zhefan Rao, Yilan Chen, Quanshi Zhang
2003.03944	Pacemaker: Intermediate Teacher Knowledge Distillation For On-The-Fly Convolutional Neural Network	Computer Vision and Pattern Recognition (cs.CV)	Wonchul Son, Youngbin Kim, Wonseok Song, Youngsu Moon, Wonjun Hwang
2003.04222	Sparse and Cosparse Audio Dequantization Using Convex Optimization	Signal Processing (eess.SP)	Pavel Záviška, Pavel Rajmic
2003.04289	Knowledge distillation via adaptive instance normalization	Computer Vision and Pattern Recognition (cs.CV)	Jing Yang, Brais Martinez, Adrian Bulat, Georgios Tzimiropoulos
2003.04510	HEAAN Demystified: Accelerating Fully Homomorphic Encryption Through Architecture-centric Analysis and Optimization	Distributed, Parallel, and Cluster Computing (cs.DC)	Wonkyung Jung, Eojin Lee, Sangpyo Kim, Keewoo Lee, Namhoon Kim, Chohong Min, Jung Hee Cheon, Jung Ho Ahn
2003.04566	Channel Pruning via Optimal Thresholding	Computer Vision and Pattern Recognition (cs.CV)	Yun Ye, Ganmei You, Jong-Kae Fwu, Xia Zhu, Qing Yang, Yuan Zhu
2003.04684	Distributed Deep Convolutional Compression for Massive MIMO CSI Feedback	Signal Processing (eess.SP)	Qianqian Yang, Mahdi Boloursaz Mashhadi, Deniz Gunduz
2003.04769	AP-MTL: Attention Pruned Multi-task Learning Model for Real-time Instrument Detection and Segmentation in Robot-assisted Surgery	Computer Vision and Pattern Recognition (cs.CV)	Mobarakol Islam, Vibashan VS, Hongliang Ren
2003.05148	Kernel Quantization for Efficient Network Compression	Machine Learning (cs.LG)	Zhongzhi Yu, Yemin Shi, Tiejun Huang, Yizhou Yu
2003.05326	Training-Set Distillation for Real-Time UAV Object Tracking	Computer Vision and Pattern Recognition (cs.CV)	Fan Li, Changhong Fu, Fuling Lin, Yiming Li, Peng Lu
2003.05891	SASL: Saliency-Adaptive Sparsity Learning for Neural Network Acceleration	Computer Vision and Pattern Recognition (cs.CV)	Jun Shi, Jianfeng Xu, Kazuyuki Tasaka, Zhibo Chen
2003.06212	Accelerating and Improving AlphaZero Using Population Based Training	Artificial Intelligence (cs.AI)	Ti-Rong Wu, Ting-Han Wei, I-Chen Wu
2003.06254	What Information Does a ResNet Compress?	Machine Learning (cs.LG)	Luke Nicholas Darlow, Amos Storkey
2003.06513	A Privacy-Preserving DNN Pruning and Mobile Acceleration Framework	Machine Learning (cs.LG)	Zheng Zhan, Yifan Gong, Zhengang Li, Pu Zhao, Xiaolong Ma, Wei Niu, Xiaolin Xu, Bin Ren, Yanzhi Wang, Xue Lin
2003.06700	CoCoPIE: Making Mobile AI Sweet As PIE --Compression-Compilation Co-Design Goes a Long Way	Machine Learning (cs.LG)	Shaoshan Liu, Bin Ren, Xipeng Shen, Yanzhi Wang
2003.06757	Channel Pruning Guided by Classification Loss and Feature Importance	Computer Vision and Pattern Recognition (cs.CV)	Jinyang Guo, Wanli Ouyang, Dong Xu
2003.07636	Verification of Neural Networks: Enhancing Scalability through Pruning	Machine Learning (cs.LG)	Dario Guidotti, Francesco Leofante, Luca Pulina, Armando Tacchella
2003.07849	Blur, Noise, and Compression Robust Generative Adversarial Networks	Computer Vision and Pattern Recognition (cs.CV)	Takuhiro Kaneko, Tatsuya Harada
2003.08436	Collaborative Distillation for Ultra-Resolution Universal Style Transfer	Computer Vision and Pattern Recognition (cs.CV)	Huan Wang, Yijun Li, Yuehai Wang, Haoji Hu, Ming-Hsuan Yang
2003.08472	MINT: Deep Network Compression via Mutual Information-based Neuron Trimming	Machine Learning (cs.LG)	Madan Ravi Ganesh, Jason J. Corso, Salimeh Yasaei Sekeh
2003.08755	Adaptive binarization based on fuzzy integrals	Computer Vision and Pattern Recognition (cs.CV)	Francesco Bardozzo, Borja De La Osa, Lubomira Horanska, Javier Fumanal-Idocin, Mattia delli Priscoli, Luigi Troiano, Roberto Tagliaferri, Javier Fernandez, Humberto Bustince
2003.08935	Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression	Computer Vision and Pattern Recognition (cs.CV)	Yawei Li, Shuhang Gu, Christoph Mayer, Luc Van Gool, Radu Timofte
2003.08936	GAN Compression: Efficient Architectures for Interactive Conditional GANs	Computer Vision and Pattern Recognition (cs.CV)	Muyang Li, Ji Lin, Yaoyao Ding, Zhijian Liu, Jun-Yan Zhu, Song Han
2003.09615	DP-Net: Dynamic Programming Guided Deep Neural Network Compression	Machine Learning (cs.LG)	Dingcheng Yang, Wenjian Yu, Ao Zhou, Haoyuan Mu, Gary Yao, Xiaoyi Wang
2003.09708	Accelerating Deep Reinforcement Learning With the Aid of a Partial Model: Power-Efficient Predictive Video Streaming	Machine Learning (cs.LG)	Dong Liu, Jianyu Zhao, Chenyang Yang, Lajos Hanzo
2003.09833	SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection	Computation and Language (cs.CL)	Xiaoya Li, Yuxian Meng, Qinghong Han, Fei Wu, Jiwei Li
2003.09896	Multi-target regression via output space quantization	Machine Learning (cs.LG)	Eleftherios Spyromitros-Xioufis, Konstantinos Sechidis, Ioannis Vlahavas
2003.10184	Learning Better Lossless Compression Using Lossy Compression	Computer Vision and Pattern Recognition (cs.CV)	Fabian Mentzer, Luc Van Gool, Michael Tschannen
2003.10477	Distilling Knowledge from Graph Convolutional Networks	Computer Vision and Pattern Recognition (cs.CV)	Yiding Yang, Jiayan Qiu, Mingli Song, Dacheng Tao, Xinchao Wang
2003.10735	ShadowTutor: Distributed Partial Distillation for Mobile Video DNN Inference	Distributed, Parallel, and Cluster Computing (cs.DC)	Jae-Won Chung, Jae-Yun Kim, Soo-Mook Moon
2003.11333	Accelerated learning algorithms of general fuzzy min-max neural network using a branch-and-bound-based hyperbox selection rule	Machine Learning (cs.LG)	Thanh Tung Khuat, Bogdan Gabrys
2003.11337	SPFCN: Select and Prune the Fully Convolutional Networks for Real-time Parking Slot Detection	Computer Vision and Pattern Recognition (cs.CV)	Zhuoping Yu, Zhong Gao, Hansheng Chen, Yuyao Huang
2003.11342	Circumventing Outliers of AutoAugment with Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Longhui Wei, An Xiao, Lingxi Xie, Xin Chen, Xiaopeng Zhang, Qi Tian
2003.11996	Accelerated Analog Neuromorphic Computing	Neural and Evolutionary Computing (cs.NE)	Johannes Schemmel, Sebastian Billaudelle, Phillip Dauer, Johannes Weis
2003.12563	DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search	Computer Vision and Pattern Recognition (cs.CV)	Xiyang Dai, Dongdong Chen, Mengchen Liu, Yinpeng Chen, Lu Yuan
2003.12621	Acceleration of Convolutional Neural Network Using FFT-Based Split Convolutions	Computer Vision and Pattern Recognition (cs.CV)	Kamran Chitsaz, Mohsen Hajabdollahi, Nader Karimi, Shadrokh Samavi, Shahram Shirani
2003.12635	The impossibility of low rank representations for triangle-rich complex networks	Machine Learning (cs.LG)	C. Seshadhri, Aneesh Sharma, Andrew Stolman, Ashish Goel
2003.13438	On the Unreasonable Effectiveness of Knowledge Distillation: Analysis in the Kernel Regime	Machine Learning (cs.LG)	Arman Rahbar, Ashkan Panahi, Chiranjib Bhattacharyya, Devdatt Dubhashi, Morteza Haghir Chehreghani
2003.13493	Faster than FAST: GPU-Accelerated Frontend for High-Speed VIO	Computer Vision and Pattern Recognition (cs.CV)	Balazs Nagy, Philipp Foehn, Davide Scaramuzza
2003.13586	Squeezed Deep 6DoF Object Detection Using Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Heitor Felix, Walber M. Rodrigues, David Macêdo, Francisco Simões, Adriano L. I. Oliveira, Veronica Teichrieb, Cleber Zanchettin
2003.13593	How Not to Give a FLOP: Combining Regularization and Pruning for Efficient Inference	Machine Learning (cs.LG)	Tai Vu, Emily Wen, Roy Nehoran
2003.13683	DHP: Differentiable Meta Pruning via HyperNetworks	Computer Vision and Pattern Recognition (cs.CV)	Yawei Li, Shuhang Gu, Kai Zhang, Luc Van Gool, Radu Timofte
2003.13942	Spatio-Temporal Graph for Video Captioning with Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Boxiao Pan, Haoye Cai, De-An Huang, Kuan-Hui Lee, Adrien Gaidon, Ehsan Adeli, Juan Carlos Niebles
2003.13960	Neural Networks Are More Productive Teachers Than Human Raters: Active Mixup for Data-Efficient Knowledge Distillation from a Blackbox Model	Computer Vision and Pattern Recognition (cs.CV)	Dongdong Wang, Yandong Li, Liqiang Wang, Boqing Gong
2003.13964	Regularizing Class-wise Predictions via Self-knowledge Distillation	Machine Learning (cs.LG)	Sukmin Yun, Jongjin Park, Kimin Lee, Jinwoo Shin
2003.14030	Distilled Semantics for Comprehensive Scene Understanding from Videos	Computer Vision and Pattern Recognition (cs.CV)	Fabio Tosi, Filippo Aleotti, Pierluigi Zama Ramirez, Matteo Poggi, Samuele Salti, Luigi Di Stefano, Stefano Mattoccia
2004.00224	Understanding GPU-Based Lossy Compression for Extreme-Scale Cosmological Simulations	Distributed, Parallel, and Cluster Computing (cs.DC)	Sian Jin, Pascal Grosset, Christopher M. Biwer, Jesus Pulido, Jiannan Tian, Dingwen Tao, James Ahrens
2004.00280	Creating Something from Nothing: Unsupervised Knowledge Distillation for Cross-Modal Hashing	Computer Vision and Pattern Recognition (cs.CV)	Hengtong Hu, Lingxi Xie, Richang Hong, Qi Tian
2004.00390	More Grounded Image Captioning by Distilling Image-Text Matching Model	Computer Vision and Pattern Recognition (cs.CV)	Yuanen Zhou, Meng Wang, Daqing Liu, Zhenzhen Hu, Hanwang Zhang
2004.00999	Pruned Wasserstein Index Generation Model and wigpy Package	Machine Learning (cs.LG)	Fangzhou Xie
2004.02088	Feature Quantization Improves GAN Training	Machine Learning (cs.LG)	Yang Zhao, Chunyuan Li, Ping Yu, Jianfeng Gao, Changyou Chen
2004.02164	DSA: More Efficient Budgeted Pruning via Differentiable Sparsity Allocation	Computer Vision and Pattern Recognition (cs.CV)	Xuefei Ning, Tianchen Zhao, Wenshuo Li, Peng Lei, Yu Wang, Huazhong Yang
2004.02178	FastBERT: a Self-distilling BERT with Adaptive Inference Time	Computation and Language (cs.CL)	Weijie Liu, Peng Zhou, Zhe Zhao, Zhiruo Wang, Haotang Deng, Qi Ju
2004.02297	Reducing Data Motion to Accelerate the Training of Deep Neural Networks	Distributed, Parallel, and Cluster Computing (cs.DC)	Sicong Zhuang, Cristiano Malossi, Marc Casas
2004.02569	Gradient-Based Training and Pruning of Radial Basis Function Networks with an Application in Materials Physics	Machine Learning (cs.LG)	Jussi Määttä, Viacheslav Bazaliy, Jyri Kimari, Flyura Djurabekova, Kai Nordlund, Teemu Roos
2004.03097	Towards Non-task-specific Distillation of BERT via Sentence Representation Approximation	Computation and Language (cs.CL)	Bowen Wu, Huan Zhang, Mengyuan Li, Zongsheng Wang, Qihang Feng, Junhong Huang, Baoxun Wang
2004.03281	Teacher-Class Network: A Neural Network Compression Mechanism	Machine Learning (cs.LG)	Shaiq Munir Malik, Mohbat Tharani, Murtaza Taj
2004.03303	Towards Efficient Unconstrained Palmprint Recognition via Deep Distillation Hashing	Computer Vision and Pattern Recognition (cs.CV)	Huikai Shao, Dexing Zhong, Xuefeng Du
2004.03376	Composition of Saliency Metrics for Channel Pruning with a Myopic Oracle	Computer Vision and Pattern Recognition (cs.CV)	Kaveena Persand, Andrew Anderson, David Gregg
2004.03846	Structure-Level Knowledge Distillation For Multilingual Sequence Labeling	Computation and Language (cs.CL)	Xinyu Wang, Yong Jiang, Nguyen Bach, Tao Wang, Fei Huang, Kewei Tu
2004.04124	LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression	Computation and Language (cs.CL)	Yihuan Mao, Yujing Wang, Chufan Wu, Chen Zhang, Yang Wang, Yaming Yang, Quanlu Zhang, Yunhai Tong, Jing Bai
2004.04342	Feedback Recurrent Autoencoder for Video Compression	Machine Learning (cs.LG)	Adam Golinski, Reza Pourreza, Yang Yang, Guillaume Sautiere, Taco S Cohen
2004.04343	Pruning and Sparsemax Methods for Hierarchical Attention Networks	Computation and Language (cs.CL)	João G. Ribeiro, Frederico S. Felisberto, Isabel C. Neto
2004.04710	Prune2Edge: A Multi-Phase Pruning Pipelines to Deep Ensemble Learning in IIoT	Machine Learning (cs.LG)	Besher Alhalabi, Mohamed Gaber, Shadi Basurra
2004.05085	Beyond Disentangled Representations: An Attentive Angular Distillation Approach to Large-scale Lightweight Age-Invariant Face Recognition	Computer Vision and Pattern Recognition (cs.CV)	Thanh-Dat Truong, Chi Nhan Duong, Kha Gia Quach, Dung Nguyen, Ngan Le, Khoa Luu, Tien D. Bui
2004.05140	One Model to Recognize Them All: Marginal Distillation from NER Models with Different Tag Sets	Computation and Language (cs.CL)	Keunwoo Peter Yu, Yi Yang
2004.05304	Inter-Region Affinity Distillation for Road Marking Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Yuenan Hou, Zheng Ma, Chunxiao Liu, Tak-Wai Hui, Chen Change Loy
2004.05333	Bit-Parallel Vector Composability for Neural Acceleration	Machine Learning (cs.LG)	Soroush Ghodrati, Hardik Sharma, Cliff Young, Nam Sung Kim, Hadi Esmaeilzadeh
2004.05531	A Unified DNN Weight Compression Framework Using Reweighted Optimization Methods	Machine Learning (cs.LG)	Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Minghai Qin, Fei Sun, Yen-Kuang Chen, Caiwen Ding, Makan Fardad, Yanzhi Wang
2004.05686	XtremeDistil: Multi-stage Distillation for Massive Multilingual Models	Computation and Language (cs.CL)	Subhabrata Mukherjee, Ahmed Awadallah
2004.05913	Blind Adversarial Pruning: Balance Accuracy, Efficiency and Robustness	Machine Learning (cs.LG)	Haidong Xie, Lixin Qian, Xueshuang Xiang, Naijin Liu
2004.05930	Technical Report: NEMO DNN Quantization for Deployment Model	Machine Learning (cs.LG)	Francesco Conti
2004.05937	Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New Outlooks	Computer Vision and Pattern Recognition (cs.CV)	Lin Wang, Kuk-Jin Yoon
2004.05962	Accelerating B-spline Interpolation on GPUs: Application to Medical Image Registration	Distributed, Parallel, and Cluster Computing (cs.DC)	Orestis Zachariadis, Andrea Teatini, Nitin Satpute, Juan Gómez-Luna, Onur Mutlu, Ole Jakob Elle, Joaquín Olivares
2004.06638	Distilling Localization for Self-Supervised Representation Learning	Computer Vision and Pattern Recognition (cs.CV)	Nanxuan Zhao, Zhirong Wu, Rynson W.H. Lau, Stephen Lin
2004.06692	Quantization Analysis and Robust Design for Distributed Graph Filters	Signal Processing (eess.SP)	Leila Ben Saad, Baltasar Beferull-Lozano, Elvin Isufi
2004.07320	Training with Quantization Noise for Extreme Model Compression	Machine Learning (cs.LG)	Angela Fan, Pierre Stock, Benjamin Graham, Edouard Grave, Remi Gribonval, Herve Jegou, Armand Joulin
2004.07324	Building a Multi-domain Neural Machine Translation Model using Knowledge Distillation	Computation and Language (cs.CL)	Idriss Mghabbar, Pirashanth Ratnamogan
2004.07544	Multimodal and multiview distillation for real-time player detection on a football field	Computer Vision and Pattern Recognition (cs.CV)	Anthony Cioppa, Adrien Deliège, Noor Ul Huda, Rikke Gade, Marc Van Droogenbroeck, Thomas B. Moeslund
2004.07711	Knowledge Distillation for Action Anticipation via Label Smoothing	Computer Vision and Pattern Recognition (cs.CV)	Guglielmo Camporese, Pasquale Coscia, Antonino Furnari, Giovanni Maria Farinella, Lamberto Ballan
2004.08116	Triplet Loss for Knowledge Distillation	Machine Learning (cs.LG)	Hideki Oki, Motoshi Abe, Junichi Miyao, Takio Kurita
2004.08151	Accelerating Physics-Informed Neural Network Training with Prior Dictionaries	Machine Learning (cs.LG)	Wei Peng, Weien Zhou, Jun Zhang, Wen Yao
2004.08552	Accurate Tumor Tissue Region Detection with Accelerated Deep Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Gabriel Tjio, Xulei Yang, Jia Mei Hong, Sum Thai Wong, Vanessa Ding, Andre Choo, Yi Su
2004.08861	Role-Wise Data Augmentation for Knowledge Distillation	Machine Learning (cs.LG)	Jie Fu, Xue Geng, Zhijian Duan, Bohan Zhuang, Xingdi Yuan, Adam Trischler, Jie Lin, Chris Pal, Hao Dong
2004.09569	Towards deep neural network compression via learnable wavelet transforms	Machine Learning (cs.LG)	Moritz Wolter ( Bonn University), Shaohui Lin ( National University of Singapore), Angela Yao ( National University of Singapore)
2004.09576	LSQ+: Improving low-bit quantization through learnable offsets and better initialization	Computer Vision and Pattern Recognition (cs.CV)	Yash Bhalgat, Jinwon Lee, Markus Nagel, Tijmen Blankevoort, Nojun Kwak
2004.09602	Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation	Machine Learning (cs.LG)	Hao Wu, Patrick Judd, Xiaojie Zhang, Mikhail Isaev, Paulius Micikevicius
2004.09813	Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation	Computation and Language (cs.CL)	Nils Reimers, Iryna Gurevych
2004.10043	Towards Analysis-friendly Face Representation with Scalable Feature and Texture Compression	Computer Vision and Pattern Recognition (cs.CV)	Shurun Wang, Shiqi Wang, Wenhan Yang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Wen Gao
2004.10171	Knowledge Distillation for Multilingual Unsupervised Neural Machine Translation	Computation and Language (cs.CL)	Haipeng Sun, Rui Wang, Kehai Chen, Masao Utiyama, Eiichiro Sumita, Tiejun Zhao
2004.10568	Up or Down? Adaptive Rounding for Post-Training Quantization	Machine Learning (cs.LG)	Markus Nagel, Rana Ali Amjad, Mart van Baalen, Christos Louizos, Tijmen Blankevoort
2004.10694	DyNet: Dynamic Convolution for Accelerating Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Yikang Zhang, Jian Zhang, Qiang Wang, Zhao Zhong
2004.10943	Distilling Knowledge from Refinement in Multiple Instance Detection Networks	Computer Vision and Pattern Recognition (cs.CV)	Luis Felipe Zeni, Claudio Jung
2004.11045	Distilling Knowledge for Fast Retrieval-based Chat-bots	Information Retrieval (cs.IR)	Amir Vakili Tahami, Kamyar Ghajar, Azadeh Shakery
2004.11233	QUANOS- Adversarial Noise Sensitivity Driven Hybrid Quantization of Neural Networks	Machine Learning (cs.LG)	Priyadarshini Panda
2004.11250	Towards Real-Time DNN Inference on Mobile Platforms with Model Pruning and Compiler Optimization	Machine Learning (cs.LG)	Wei Niu, Pu Zhao, Zheng Zhan, Xue Lin, Yanzhi Wang, Bin Ren
2004.11506	Automatic low-bit hybrid quantization of neural networks through meta learning	Machine Learning (cs.LG)	Tao Wang, Junsong Wang, Chang Xu, Chao Xue
2004.11627	Convolution-Weight-Distribution Assumption: Rethinking the Criteria of Channel Pruning	Machine Learning (cs.LG)	Zhongzhan Huang, Xinjiang Wang, Ping Luo
2004.11783	Quantization of Deep Neural Networks for Accumulator-constrained Processors	Computer Vision and Pattern Recognition (cs.CV)	Barry de Bruin, Zoran Zivkovic, Henk Corporaal
2004.12311	DGD: Densifying the Knowledge of Neural Networks with Filter Grafting and Knowledge Distillation	Machine Learning (cs.LG)	Hao Cheng, Fanxu Meng, Ke Li, Huixiang Luo, Guangming Lu, Xiaowei Guo, Feiyue Huang, Xing Sun
2004.12817	LightPAFF: A Two-Stage Distillation Framework for Pre-training and Fine-tuning	Computation and Language (cs.CL)	Kaitao Song, Hao Sun, Xu Tan, Tao Qin, Jianfeng Lu, Hongzhi Liu, Tie-Yan Liu
2004.12909	Evolutionary Stochastic Policy Distillation	Machine Learning (cs.LG)	Hao Sun, Xinyu Pan, Bo Dai, Dahua Lin, Bolei Zhou
2004.12993	DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference	Computation and Language (cs.CL)	Ji Xin, Raphael Tang, Jaejun Lee, Yaoliang Yu, Jimmy Lin
2004.13027	FlexSA: Flexible Systolic Array Architecture for Efficient Pruned DNN Model Training	Machine Learning (cs.LG)	Sangkug Lym, Mattan Erez
2004.13139	A Generic Network Compression Framework for Sequential Recommender Systems	Information Retrieval (cs.IR)	Yang Sun, Fajie Yuan, Min Yang, Guoao Wei, Zhou Zhao, Duo Liu
2004.13401	CmnRec: Sequential Recommendations with Chunk-accelerated Memory Network	Information Retrieval (cs.IR)	Shilin Qu, Fajie Yuan, Guibing Guo, Liguang Zhang, Wei Wei
2004.13653	GPU-Accelerated Compression and Visualization of Large-Scale Vessel Trajectories in Maritime IoT Industries	Signal Processing (eess.SP)	Yu Huang, Yan Li, Zhaofeng Zhang, Ryan Wen Liu
2004.13770	Streamlining Tensor and Network Pruning in PyTorch	Machine Learning (cs.LG)	Michela Paganini, Jessica Forde
2004.14340	WoodFisher: Efficient second-order approximations for model compression	Machine Learning (cs.LG)	Sidak Pal Singh, Dan Alistarh
2004.14492	Rethinking Class-Discrimination Based CNN Channel Pruning	Computer Vision and Pattern Recognition (cs.CV)	Yuchen Liu, David Wentzlaff, S.Y. Kung
2004.14566	TRP: Trained Rank Pruning for Efficient Deep Neural Networks	Machine Learning (cs.LG)	Yuhui Xu, Yuxi Li, Shuai Zhang, Wei Wen, Botao Wang, Yingyong Qi, Yiran Chen, Weiyao Lin, Hongkai Xiong
2004.14584	Out-of-the-box channel pruned networks	Machine Learning (cs.LG)	Ragav Venkatesan, Gurumurthy Swaminathan, Xiong Zhou, Anna Luo
2004.14765	Pruning artificial neural networks: a way to find well-generalizing, high-entropy sharp minima	Machine Learning (cs.LG)	Enzo Tartaglione, Andrea Bragagnolo, Marco Grangetto
2005.00288	Distilling Spikes: Knowledge Distillation in Spiking Neural Networks	Neural and Evolutionary Computing (cs.NE)	Ravi Kumar Kushawaha, Saurabh Kumar, Biplab Banerjee, Rajbabu Velmurugan
2005.00727	Heterogeneous Knowledge Distillation using Information Flow Modeling	Computer Vision and Pattern Recognition (cs.CV)	Nikolaos Passalis, Maria Tzelepi, Anastasios Tefas
2005.00797	Multi-consensus Decentralized Accelerated Gradient Descent	Machine Learning (cs.LG)	Haishan Ye, Luo Luo, Ziang Zhou, Tong Zhang
2005.00955	How Can We Accelerate Progress Towards Human-like Linguistic Generalization?	Computation and Language (cs.CL)	Tal Linzen
2005.00974	Quadtree Driven Lossy Event Compression	Computer Vision and Pattern Recognition (cs.CV)	Srutarshi Banerjee, Zihao W. Wang, Henry H. Chopp, Oliver Cossairt, Aggelos Katsaggelos
2005.01432	Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation	Machine Learning (cs.LG)	Hany Abdulsamad, Jan Peters
2005.01864	Streaming Object Detection for 3-D Point Clouds	Computer Vision and Pattern Recognition (cs.CV)	Wei Han, Zhengdong Zhang, Benjamin Caine, Brandon Yang, Christoph Sprunk, Ouais Alsharif, Jiquan Ngiam, Vijay Vasudevan, Jonathon Shlens, Zhifeng Chen
2005.02177	CDC: Classification Driven Compression for Bandwidth Efficient Edge-Cloud Collaborative Deep Learning	Machine Learning (cs.LG)	Yuanrui Dong, Peng Zhao, Hanqiao Yu, Cong Zhao, Shusen Yang
2005.02634	Dependency Aware Filter Pruning	Computer Vision and Pattern Recognition (cs.CV)	Kai Zhao, Xin-Yu Zhang, Qi Han, Ming-Ming Cheng
2005.03354	DMCP: Differentiable Markov Channel Pruning for Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Shaopeng Guo, Yujie Wang, Quanquan Li, Junjie Yan
2005.03848	Distilling Knowledge from Pre-trained Language Models via Text Smoothing	Computation and Language (cs.CL)	Xing Wu, Yibing Liu, Xiangyang Zhou, Dianhai Yu
2005.03858	Compressing Large Sample Data for Discriminant Analysis	Machine Learning (stat.ML)	Alexander F. Lapanowski, Irina Gaynanova
2005.04064	Lossy Compression with Distortion Constrained Optimization	Machine Learning (cs.LG)	Ties van Rozendaal, Guillaume Sautière, Taco S. Cohen
2005.04098	Near Memory Acceleration on High Resolution Radio Astronomy Imaging	Distributed, Parallel, and Cluster Computing (cs.DC)	Stefano Corda, Bram Veenboer, Ahsan Javed Awan, Akash Kumar, Roel Jordans, Henk Corporaal
2005.04136	Data-Free Network Quantization With Adversarial Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yoojin Choi, Jihwan Choi, Mostafa El-Khamy, Jungwon Lee
2005.04275	Pruning Algorithms to Accelerate Convolutional Neural Networks for Edge Applications: A Survey	Machine Learning (cs.LG)	Jiayi Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah
2005.04347	GPU Acceleration of Sparse Neural Networks	Distributed, Parallel, and Cluster Computing (cs.DC)	Aavaas Gajurel, Sushil J. Louis, Frederick C Harris
2005.04355	Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising	Distributed, Parallel, and Cluster Computing (cs.DC)	Xiaotian Hao, Junqi Jin, Jianye Hao, Jin Li, Weixun Wang, Yi Ma, Zhenzhe Zheng, Han Li, Jian Xu, Kun Gai
2005.04366	Compressing Recurrent Neural Networks Using Hierarchical Tucker Tensor Decomposition	Machine Learning (cs.LG)	Miao Yin, Siyu Liao, Xiao-Yang Liu, Xiaodong Wang, Bo Yuan
2005.04559	Compact Neural Representation Using Attentive Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Mahdi Biparva, John Tsotsos
2005.05276	CupNet -- Pruning a network for geometric data	Machine Learning (cs.LG)	Raoul Heese, Lukas Morand, Dirk Helm, Michael Bortz
2005.05418	Optimizing Vessel Trajectory Compression	Computer Vision and Pattern Recognition (cs.CV)	Giannis Fikioris, Kostas Patroumpas, Alexander Artikis
2005.05704	Fostering Event Compression using Gated Surprise	Machine Learning (cs.LG)	Dania Humaidan, Sebastian Otte, Martin V. Butz
2005.05898	Learning to Estimate Driver Drowsiness from Car Acceleration Sensors using Weakly Labeled Data	Machine Learning (cs.LG)	Takayuki Katsuki, Kun Zhao, Takayuki Yoshizumi
2005.06105	Proxy Experience Replay: Federated Distillation for Distributed Reinforcement Learning	Machine Learning (cs.LG)	Han Cha, Jihong Park, Hyesung Kim, Mehdi Bennis, Seong-Lyun Kim
2005.06284	Artificial Neural Network Pruning to Extract Knowledge	Machine Learning (cs.LG)	Evgeny M Mirkes
2005.07093	Bayesian Bits: Unifying Quantization and Pruning	Machine Learning (cs.LG)	Mart van Baalen, Christos Louizos, Markus Nagel, Rana Ali Amjad, Ying Wang, Tijmen Blankevoort, Max Welling
2005.07111	Distilling neural networks into skipgram-level decision lists	Computation and Language (cs.CL)	Madhumita Sushil, Simon Šuster, Walter Daelemans
2005.07133	PENNI: Pruned Kernel Sharing for Efficient CNN Inference	Computer Vision and Pattern Recognition (cs.CV)	Shiyu Li, Edward Hanson, Hai Li, Yiran Chen
2005.07259	A Reconstruction-Computation-Quantization (RCQ) Approach to Node Operations in LDPC Decoding	Signal Processing (eess.SP)	Linfang Wang, Maximilian Stark, Richard D. Wesel, Gerhard Bauch
2005.07683	Movement Pruning: Adaptive Sparsity by Fine-Tuning	Computation and Language (cs.CL)	Victor Sanh, Thomas Wolf, Alexander M. Rush
2005.07786	A flexible, extensible software framework for model compression based on the LC algorithm	Machine Learning (cs.LG)	Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
2005.07839	Joint Progressive Knowledge Distillation and Unsupervised Domain Adaptation	Machine Learning (cs.LG)	Le Thanh Nguyen-Meidine, Eric Granger, Madhu Kiran, Jose Dolz, Louis-Antoine Blais-Morin
2005.07925	Spatiotemporal Adaptive Quantization for Video Compression Applications	Multimedia (cs.MM)	Lee Prangnell
2005.07928	Spatiotemporal Adaptive Quantization for the Perceptual Video Coding of RGB 4:4:4 Data	Multimedia (cs.MM)	Lee Prangnell, Victor Sanchez
2005.08110	Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks	Machine Learning (cs.LG)	Meet P. Vadera, Brian Jalaian, Benjamin M. Marlin
2005.08213	Speech to Text Adaptation: Towards an Efficient Cross-Modal Distillation	Computation and Language (cs.CL)	Won Ik Cho, Donghyun Kwak, Jiwon Yoon, Nam Soo Kim
2005.08501	VecQ: Minimal Loss DNN Model Compression With Vectorized Weight Quantization	Computer Vision and Pattern Recognition (cs.CV)	Cheng Gong, Yao Chen, Ye Lu, Tao Li, Cong Hao, Deming Chen
2005.08898	Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent	Machine Learning (cs.LG)	Tian Tong, Cong Ma, Yuejie Chi
2005.08931	Joint Multi-Dimension Pruning	Computer Vision and Pattern Recognition (cs.CV)	Zechun Liu, Xiangyu Zhang, Zhiqiang Shen, Zhe Li, Yichen Wei, Kwang-Ting Cheng, Jian Sun
2005.09034	Cross-filter compression for CNN inference acceleration	Computer Vision and Pattern Recognition (cs.CV)	Fuyuan Lyu, Shien Zhu, Weichen Liu
2005.09163	Learning from a Lightweight Teacher for Efficient Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yuang Liu, Wei Zhang, Jun Wang
2005.09310	Distilling Knowledge from Ensembles of Acoustic Models for Joint CTC-Attention End-to-End Speech Recognition	Machine Learning (cs.LG)	Yan Gao, Titouan Parcollet, Nicholas Lane
2005.09453	Experience Augmentation: Boosting and Accelerating Off-Policy Multi-Agent Reinforcement Learning	Machine Learning (cs.LG)	Zhenhui Ye, Yining Chen, Guanghua Song, Bowei Yang, Shen Fan
2005.10419	Why distillation helps: a statistical perspective	Machine Learning (cs.LG)	Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Seungyeon Kim, Sanjiv Kumar
2005.10451	CPOT: Channel Pruning via Optimal Transport	Machine Learning (cs.LG)	Yucong Shen, Li Shen, Hao-Zhi Huang, Xuan Wang, Wei Liu
2005.10615	Accelerated Convergence for Counterfactual Learning to Rank	Machine Learning (cs.LG)	Rolf Jagerman, Maarten de Rijke
2005.10985	Deep learning application of vibration data for predictive maintenance of gravity acceleration equipment	Signal Processing (eess.SP)	SeonWoo Lee, YuHyeon Tak, HoJun Yang, JaeHeung Yang, GangMin Lim, KyuSung Kim, ByeongKeun Choi, JangWoo Kwon
2005.11035	Position-based Scaled Gradient for Model Quantization and Sparse Training	Computer Vision and Pattern Recognition (cs.CV)	Jangho Kim, KiYoon Yoo, Nojun Kwak
2005.11248	Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics	Machine Learning (cs.LG)	Payel Das, Tom Sercu, Kahini Wadhawan, Inkit Padhi, Sebastian Gehrmann, Flaviu Cipcigan, Vijil Chenthamarakshan, Hendrik Strobelt, Cicero dos Santos, Pin-Yu Chen, Yi Yan Yang, Jeremy Tan, James Hedrick, Jason Crain, Aleksandra Mojsilovic
2005.11282	PruneNet: Channel Pruning via Global Importance	Machine Learning (cs.LG)	Ashish Khetan, Zohar Karnin
2005.11619	Bayesian Neural Networks at Scale: A Performance Analysis and Pruning Study	Machine Learning (cs.LG)	Himanshu Sharma, Elise Jennings
2005.11638	Joint learning of interpretation and distillation	Machine Learning (cs.LG)	Jinchao Huang, Guofu Li, Zhicong Yan, Fucai Luo, Shenghong Li
2005.11704	MIMO Speech Compression and Enhancement Based on Convoltuional Denoising Autoencoder	Audio and Speech Processing (eess.AS)	You-Jin Li, Syu-Siang Wang, Yu Tsao, Borching Su
2005.12193	Feature Statistics Guided Efficient Filter Pruning	Machine Learning (cs.LG)	Hang Li, Chen Ma, Wei Xu, Xue Liu
2005.12364	Distributed Resource Scheduling for Large-Scale MEC Systems: A Multi-Agent Ensemble Deep Reinforcement Learning with Imitation Acceleration	Distributed, Parallel, and Cluster Computing (cs.DC)	Feibo Jiang, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan
2005.12553	Efficient Use of heuristics for accelerating XCS-based Policy Learning in Markov Games	Artificial Intelligence (cs.AI)	Hao Chen, Chang Wang, Jian Huang, Jianxing Gong
2005.13297	Accelerating Neural Network Inference by Overflow Aware Quantization	Computer Vision and Pattern Recognition (cs.CV)	Hongwei Xie, Shuo Zhang, Huanghao Ding, Yafei Song, Baitao Shao, Conggang Hu, Ling Cai, Mingyang Li
2005.13482	Syntactic Structure Distillation Pretraining For Bidirectional Encoders	Computation and Language (cs.CL)	Adhiguna Kuncoro, Lingpeng Kong, Daniel Fried, Dani Yogatama, Laura Rimell, Chris Dyer, Phil Blunsom
2005.13746	CPAC-Conv: CP-decomposition to Approximately Compress Convolutional Layers in Deep Learning	Machine Learning (cs.LG)	Yinan Wang, Weihong (Grace)Guo, Xiaowei Yue
2005.13796	A Feature-map Discriminant Perspective for Pruning Deep Neural Networks	Machine Learning (cs.LG)	Zejiang Hou, Sun-Yuan Kung
2005.14070	Exploiting Non-Linear Redundancy for Neural Model Compression	Machine Learning (cs.LG)	Muhammad A. Shah, Raphael Olivier, Bhiksha Raj
2005.14435	Sub-band Knowledge Distillation Framework for Speech Enhancement	Audio and Speech Processing (eess.AS)	Xiang Hao, Shixue Wen, Xiangdong Su, Yun Liu, Guanglai Gao, Xiaofei Li
2006.00423	A New Accelerated Stochastic Gradient Method with Momentum	Machine Learning (cs.LG)	Liang Liu, Xiaopeng Luo
2006.00555	Transferring Inductive Biases through Knowledge Distillation	Machine Learning (cs.LG)	Samira Abnar, Mostafa Dehghani, Willem Zuidema
2006.00844	Distilling Neural Networks for Greener and Faster Dependency Parsing	Computation and Language (cs.CL)	Mark Anderson, Carlos Gómez-Rodríguez
2006.00896	Pruning via Iterative Ranking of Sensitivity Statistics	Machine Learning (cs.LG)	Stijn Verdenius, Maarten Stol, Patrick Forré
2006.01683	Channel Distillation: Channel-Wise Attention for Knowledge Distillation	Machine Learning (cs.LG)	Zaida Zhou, Chaoran Zhuge, Xinwei Guan, Wen Liu
2006.01795	Shapley Value as Principled Metric for Structured Network Pruning	Machine Learning (cs.LG)	Marco Ancona, Cengiz Öztireli, Markus Gross
2006.01819	Acceleration of Descent-based Optimization Algorithms via Carathéodory's Theorem	Machine Learning (cs.LG)	Francesco Cosentino, Harald Oberhauser, Alessandro Abate
2006.02768	Weight Pruning via Adaptive Sparsity Loss	Machine Learning (cs.LG)	George Retsinas, Athena Elafrou, Georgios Goumas, Petros Maragos
2006.02901	A Polynomial Neural network with Controllable Precision and Human-Readable Topology II: Accelerated Approach Based on Expanded Layer	Machine Learning (cs.LG)	Gang Liu, Jing Wang
2006.02965	End-to-End Speech-Translation with Knowledge Distillation: FBK@IWSLT2020	Computation and Language (cs.CL)	Marco Gaido, Mattia Antonino Di Gangi, Matteo Negri, Marco Turchi
2006.03262	UVeQFed: Universal Vector Quantization for Federated Learning	Machine Learning (cs.LG)	Nir Shlezinger, Mingzhe Chen, Yonina C. Eldar, H. Vincent Poor, Shuguang Cui
2006.03669	An Overview of Neural Network Compression	Machine Learning (cs.LG)	James O' Neill
2006.03701	Accelerating Natural Language Understanding in Task-Oriented Dialog	Computation and Language (cs.CL)	Ojas Ahuja, Shrey Desai
2006.03810	An Empirical Analysis of the Impact of Data Augmentation on Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Deepan Das, Haley Massa, Abhimanyu Kulkarni, Theodoros Rekatsinas
2006.04061	Dual Policy Distillation	Machine Learning (cs.LG)	Kwei-Herng Lai, Daochen Zha, Yuening Li, Xia Hu
2006.04093	Multi-view Contrastive Learning for Online Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Chuanguang Yang, Zhulin An, Xiaolong Hu, Hui Zhu, Kaiqiang Xu, Yongjun Xu
2006.04127	ADMP: An Adversarial Double Masks Based Pruning Framework For Unsupervised Cross-Domain Compression	Computer Vision and Pattern Recognition (cs.CV)	Xiaoyu Feng, Zhuqing Yuan, Guijin Wang, Yongpan Liu
2006.04147	Peer Collaborative Learning for Online Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Guile Wu, Shaogang Gong
2006.04154	VQVC+: One-Shot Voice Conversion by Vector Quantization and U-Net architecture	Audio and Speech Processing (eess.AS)	Da-Yi Wu, Yen-Hao Chen, Hung-Yi Lee
2006.04270	EDropout: Energy-Based Dropout and Pruning of Deep Neural Networks	Machine Learning (cs.LG)	Hojjat Salehinejad, Shahrokh Valaee
2006.04432	AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles	Machine Learning (cs.LG)	Sicong Liu, Junzhao Du, Kaiming Nan, ZimuZhou, Atlas Wang, Yingyan Lin
2006.04451	Novel Adaptive Binary Search Strategy-First Hybrid Pyramid- and Clustering-Based CNN Filter Pruning Method without Parameters Setting	Computer Vision and Pattern Recognition (cs.CV)	Kuo-Liang Chung, Yu-Lun Chang, Bo-Wei Tsai
2006.04472	Accelerated Search for Non-Negative Greedy Sparse Decomposition via Dimensionality Reduction	Signal Processing (eess.SP)	Konstantinos Voulgaris, Mike E. Davies, Mehrdad Yaghoobi
2006.04551	Cracking the Black Box: Distilling Deep Sports Analytics	Machine Learning (cs.LG)	Xiangyu Sun, Jack Davis, Oliver Schulte, Guiliang Liu
2006.04588	EDCompress: Energy-Aware Model Compression with Dataflow	Machine Learning (cs.LG)	Zhehui Wang, Tao Luo, Joey Tianyi Zhou, Rick Siow Mong Goh
2006.04719	ResKD: Residual-Guided Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Xuewei Li, Songyuan Li, Bourahla Omar, Xi Li
2006.04753	Approximate learning of high dimensional Bayesian network structures via pruning of Candidate Parent Sets	Artificial Intelligence (cs.AI)	Zhigao Guo, Anthony C. Constantinou
2006.04920	Survival regression with accelerated failure time model in XGBoost	Machine Learning (cs.LG)	Avinash Barnwal, Hyunsu Cho, Toby Dylan Hocking
2006.04981	A Framework for Neural Network Pruning Using Gibbs Distributions	Machine Learning (cs.LG)	Alex Labach, Shahrokh Valaee
2006.05065	Self-Distillation as Instance-Specific Label Smoothing	Machine Learning (cs.LG)	Zhilu Zhang, Mert R. Sabuncu
2006.05210	Neural Network Activation Quantization with Bitwise Information Bottlenecks	Computer Vision and Pattern Recognition (cs.CV)	Xichuan Zhou, Kui Liu, Cong Shi, Haijun Liu, Ji Liu
2006.05352	Design Challenges of Neural Network Acceleration Using Stochastic Computing	Signal Processing (eess.SP)	Alireza Khadem
2006.05467	Pruning neural networks without any data by iteratively conserving synaptic flow	Machine Learning (cs.LG)	Hidenori Tanaka, Daniel Kunin, Daniel L. K. Yamins, Surya Ganguli
2006.05525	Knowledge Distillation: A Survey	Machine Learning (cs.LG)	Jianping Gou, Baosheng Yu, Stephen John Maybank, Dacheng Tao
2006.05691	Low Rank Directed Acyclic Graphs and Causal Structure Learning	Machine Learning (cs.LG)	Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He
2006.06185	JIT-Masker: Efficient Online Distillation for Background Matting	Computer Vision and Pattern Recognition (cs.CV)	Jo Chuang, Qian Dong
2006.06443	Convolutional neural networks compression with low rank and sparse tensor decompositions	Computer Vision and Pattern Recognition (cs.CV)	Pavel Kaloshin
2006.06608	GNNAdvisor: An Efficient Runtime System for GNN Acceleration on GPUs	Distributed, Parallel, and Cluster Computing (cs.DC)	Yuke Wang, Boyuan Feng, Gushu Li, Shuangchen Li, Lei Deng, Yuan Xie, Yufei Ding
2006.07114	Knowledge Distillation Meets Self-Supervision	Computer Vision and Pattern Recognition (cs.CV)	Guodong Xu, Ziwei Liu, Xiaoxiao Li, Chen Change Loy
2006.07242	Ensemble Distillation for Robust Model Fusion in Federated Learning	Machine Learning (cs.LG)	Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi
2006.07253	Dynamic Model Pruning with Feedback	Machine Learning (cs.LG)	Tao Lin, Sebastian U. Stich, Luis Barba, Daniil Dmitriev, Martin Jaggi
2006.07755	Recurrent Distillation based Crowd Counting	Computer Vision and Pattern Recognition (cs.CV)	Yue Gu, Wenxi Liu
2006.08198	AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks	Computer Vision and Pattern Recognition (cs.CV)	Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan Lin, Zhangyang Wang
2006.08341	Multi-fidelity Neural Architecture Search with Knowledge Distillation	Machine Learning (cs.LG)	Ilya Trofimov, Nikita Klyuchnikov, Mikhail Salnikov, Alexander Filippov, Evgeny Burnaev
2006.08509	APQ: Joint Search for Network Architecture, Pruning and Quantization Policy	Machine Learning (cs.LG)	Tianzhe Wang, Kuan Wang, Han Cai, Ji Lin, Zhijian Liu, Song Han
2006.08572	Flexible Dataset Distillation: Learn Labels Instead of Images	Machine Learning (cs.LG)	Ondrej Bohdal, Yongxin Yang, Timothy Hospedales
2006.08781	Optimizing variational representations of divergences and accelerating their statistical estimation	Machine Learning (cs.LG)	Jeremiah Birrell, Markos A. Katsoulakis, Yannis Pantazis
2006.08861	GPU-accelerated Hierarchical Panoramic Image Feature Retrieval for Indoor Localization	Computer Vision and Pattern Recognition (cs.CV)	Feng Hu
2006.08878	CNN Acceleration by Low-rank Approximation with Quantized Factors	Computer Vision and Pattern Recognition (cs.CV)	Nikolay Kozyrskiy, Anh-Huy Phan
2006.08950	Federated Accelerated Stochastic Gradient Descent	Machine Learning (cs.LG)	Honglin Yuan, Tengyu Ma
2006.09029	Real-time Universal Style Transfer on High-resolution Images via Zero-channel Pruning	Computer Vision and Pattern Recognition (cs.CV)	Jie An, Tao Li, Haozhi Huang, Li Shen, Xuan Wang, Yongyi Tang, Jinwen Ma, Wei Liu, Jiebo Luo
2006.09043	Improved Deep Point Cloud Geometry Compression	Computer Vision and Pattern Recognition (cs.CV)	Maurice Quach, Giuseppe Valenzise, Frederic Dufaux
2006.09054	Quantization of Acoustic Model Parameters in Automatic Speech Recognition Framework	Audio and Speech Processing (eess.AS)	Amrutha Prasad, Petr Motlicek, Srikanth Madikeri
2006.09230	Hessian-Free High-Resolution Nesterov Acceleration for Sampling	Machine Learning (cs.LG)	Ruilin Li, Hongyuan Zha, Molei Tao
2006.09247	Prior knowledge distillation based on financial time series	Machine Learning (cs.LG)	Jie Fang, Jianwu Lin
2006.09264	Bonsai-Net: One-Shot Neural Architecture Search via Differentiable Pruners	Machine Learning (cs.LG)	Rob Geada, Dennis Prangle, Andrew Stephen McGough
2006.09358	Directional Pruning of Deep Neural Networks	Machine Learning (cs.LG)	Shih-Kang Chao, Zhanyu Wang, Yue Xing, Guang Cheng
2006.09359	Accelerating Online Reinforcement Learning with Offline Datasets	Machine Learning (cs.LG)	Ashvin Nair, Murtaza Dalal, Abhishek Gupta, Sergey Levine
2006.09675	A Real-time Action Representation with Temporal Encoding and Deep Compression	Computer Vision and Pattern Recognition (cs.CV)	Kun Liu, Wu Liu, Huadong Ma, Mingkui Tan, Chuang Gan
2006.09679	StatAssist & GradBoost: A Study on Optimal INT8 Quantization-aware Training from Scratch	Machine Learning (cs.LG)	Taehoon Kim, Youngjoon Yoo, Jihoon Yang
2006.09785	Self-supervised Knowledge Distillation for Few-shot Learning	Computer Vision and Pattern Recognition (cs.CV)	Jathushan Rajasegaran, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Mubarak Shah
2006.09801	Mix2FLD: Downlink Federated Learning After Uplink Federated Distillation With Two-Way Mixup	Machine Learning (cs.LG)	Seungeun Oh, Jihong Park, Eunjeong Jeong, Hyesung Kim, Mehdi Bennis, Seong-Lyun Kim
2006.09952	Universally Quantized Neural Compression	Machine Learning (stat.ML)	Eirikur Agustsson, Lucas Theis
2006.10273	A Tutorial on VAEs: From Bayes' Rule to Lossless Compression	Machine Learning (cs.LG)	Ronald Yu
2006.10502	Distillation of neural network models for detection and description of key points of images	Computer Vision and Pattern Recognition (cs.CV)	A.V. Yashchenko, A.V. Belikov, M.V. Peterson, A.S. Potapov
2006.10518	Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming	Machine Learning (cs.LG)	Itay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, Daniel Soudry
2006.10621	On the Predictability of Pruning Across Scales	Machine Learning (cs.LG)	Jonathan S. Rosenfeld, Jonathan Frankle, Michael Carbin, Nir Shavit
2006.10814	FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs	Machine Learning (cs.LG)	Alekh Agarwal, Sham Kakade, Akshay Krishnamurthy, Wen Sun
2006.10829	Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula	Machine Learning (stat.ML)	Yuxuan Zhao, Madeleine Udell
2006.10903	Exploring Weight Importance and Hessian Bias in Model Pruning	Machine Learning (cs.LG)	Mingchen Li, Yahya Sattar, Christos Thrampoulidis, Samet Oymak
2006.11487	Paying more attention to snapshots of Iterative Pruning: Improving Model Compression via Ensemble Distillation	Computer Vision and Pattern Recognition (cs.CV)	Duong H. Le, Vo Trung Nhan, Nam Thoai
2006.11645	Accelerating Safe Reinforcement Learning with Constraint-mismatched Policies	Machine Learning (cs.LG)	Tsung-Yen Yang, Justinian Rosca, Karthik Narasimhan, Peter J. Ramadge
2006.11812	Subspace Clustering for Action Recognition with Covariance Representations and Temporal Pruning	Computer Vision and Pattern Recognition (cs.CV)	Giancarlo Paoletti, Jacopo Cavazza, Cigdem Beyan, Alessio Del Bue
2006.11967	Exploiting Weight Redundancy in CNNs: Beyond Pruning and Quantization	Machine Learning (cs.LG)	Yuan Wen, David Gregg
2006.12000	Self-Knowledge Distillation: A Simple Way for Better Generalization	Machine Learning (cs.LG)	Kyungyul Kim, ByeongMoon Ji, Doyoung Yoon, Sangheum Hwang
2006.12139	Rapid Structural Pruning of Neural Networks with Set-based Task-Adaptive Meta-Pruning	Machine Learning (cs.LG)	Minyoung Song, Jaehong Yoon, Eunho Yang, Sung Ju Hwang
2006.12156	Logarithmic Pruning is All You Need	Machine Learning (cs.LG)	Laurent Orseau, Marcus Hutter, Omar Rivasplata
2006.12279	Revisiting Loss Modelling for Unstructured Pruning	Machine Learning (cs.LG)	César Laurent, Camille Ballas, Thomas George, Nicolas Ballas, Pascal Vincent
2006.12285	Human-Expert-Level Brain Tumor Detection Using Deep Learning with Data Distillation and Augmentation	Computer Vision and Pattern Recognition (cs.CV)	Diyuan Lu, Nenad Polomac, Iskra Gacheva, Elke Hattingen, Jochen Triesch
2006.12341	Compression Algorithm Based on Irregular Sequence	Signal Processing (eess.SP)	Rui Zhu
2006.12459	IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression	Machine Learning (cs.LG)	Rianne van den Berg, Alexey A. Gritsenko, Mostafa Dehghani, Casper Kaae Sønderby, Tim Salimans
2006.12714	On Compression Principle and Bayesian Optimization for Neural Networks	Machine Learning (cs.LG)	Michael Tetelman
2006.12919	Distance Correlation Sure Independence Screening for Accelerated Feature Selection in Parkinson's Disease Vocal Data	Machine Learning (cs.LG)	Dan Schellhas, Bishal Neupane, Deepak Thammineni, Bhargav Kanumuri, Robert C. Green II
2006.12963	PFGDF: Pruning Filter via Gaussian Distribution Feature for Deep Neural Networks Acceleration	Computer Vision and Pattern Recognition (cs.CV)	Jianrong Xu, Chao Li, Bifeng Cui, Kang Yang, Yongjun Xu
2006.13108	Distilling Object Detectors with Task Adaptive Regularization	Computer Vision and Pattern Recognition (cs.CV)	Ruoyu Sun, Fuhui Tang, Xiaopeng Zhang, Hongkai Xiong, Qi Tian
2006.13484	Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes	Machine Learning (cs.LG)	Shuai Zheng, Haibin Lin, Sheng Zha, Mu Li
2006.14239	Fine granularity access in interactive compression of 360-degree images based on rate adaptive channel codes	Multimedia (cs.MM)	Navid Mahmoudian Bidgoli, Thomas Maugey, Aline Roumy
2006.14284	Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation	Machine Learning (cs.LG)	Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola
2006.14350	Data-dependent Pruning to find the Winning Lottery Ticket	Machine Learning (cs.LG)	Dániel Lévai, Zsolt Zombori
2006.14371	Accelerating Training in Artificial Neural Networks with Dynamic Mode Decomposition	Machine Learning (cs.LG)	Mauricio E. Tano, Gavin D. Portwood, Jean C. Ragusa
2006.14591	Artemis: tight convergence guarantees for bidirectional compression in Federated Learning	Machine Learning (cs.LG)	Constantin Philippenko, Aymeric Dieuleveut
2007.00192	Personalization of Hearing Aid Compression by Human-In-Loop Deep Reinforcement Learning	Audio and Speech Processing (eess.AS)	Nasim Alamdari, Edward Lobarinas, Nasser Kehtarnavaz
2007.00232	Linear Convergent Decentralized Optimization with Compression	Machine Learning (cs.LG)	Xiaorui Liu, Yao Li, Rongrong Wang, Jiliang Tang, Ming Yan
2007.00389	Single Shot Structured Pruning Before Training	Machine Learning (cs.LG)	Joost van Amersfoort, Milad Alizadeh, Sebastian Farquhar, Nicholas Lane, Yarin Gal
2007.00699	Accelerated Message Passing for Entropy-Regularized MAP Inference	Machine Learning (cs.LG)	Jonathan N. Lee, Aldo Pacchiano, Peter Bartlett, Michael I. Jordan
2007.01055	Bayesian Low Rank Tensor Ring Model for Image Completion	Machine Learning (stat.ML)	Zhen Long, Ce Zhu, Jiani Liu, Yipeng Liu
2007.01154	Federated Learning with Compression: Unified Analysis and Sharp Guarantees	Machine Learning (cs.LG)	Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari, Mehrdad Mahdavi
2007.01476	Interactive Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Shipeng Fu, Zhen Li, Jun Xu, Ming-Ming Cheng, Zitao Liu, Xiaomin Yang
2007.01486	Learning to Prune in Training via Dynamic Channel Propagation	Computer Vision and Pattern Recognition (cs.CV)	Shibo Shen, Rongpeng Li, Zhifeng Zhao, Honggang Zhang, Yugeng Zhou
2007.01491	Self-Supervised GAN Compression	Machine Learning (cs.LG)	Chong Yu, Jeff Pool
2007.01696	Channel Compression: Rethinking Information Redundancy among Channels in CNN Architecture	Machine Learning (cs.LG)	Jinhua Liang, Tao Zhang, Guoqing Feng
2007.01903	Model Distillation for Revenue Optimization: Interpretable Personalized Pricing	Machine Learning (stat.ML)	Max Biggs, Wei Sun, Markus Ettl
2007.01922	Knowledge Distillation Beyond Model Compression	Machine Learning (cs.LG)	Fahad Sarfraz, Elahe Arani, Bahram Zonooz
2007.01951	Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Liwei Wang, Jing Huang, Yin Li, Kun Xu, Zhengyuan Yang, Dong Yu
2007.01990	Accelerating Nonconvex Learning via Replica Exchange Langevin Diffusion	Machine Learning (stat.ML)	Yi Chen, Jinglin Chen, Jing Dong, Jian Peng, Zhaoran Wang
2007.02017	FracBits: Mixed Precision Quantization via Fractional Bit-Widths	Computer Vision and Pattern Recognition (cs.CV)	Linjie Yang, Qing Jin
2007.02038	Low Rank Fusion based Transformers for Multimodal Sequences	Computation and Language (cs.CL)	Saurav Sahay, Eda Okur, Shachi H Kumar, Lama Nachman
2007.02066	Weight-dependent Gates for Differentiable Neural Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Yun Li, Weiqun Wu, Zechun Liu, Chi Zhang, Xiangyu Zhang, Haotian Yao, Baoqun Yin
2007.02449	Momentum Accelerates Evolutionary Dynamics	Machine Learning (cs.LG)	Marc Harper, Joshua Safyan
2007.02491	EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Bailin Li, Bowen Wu, Jiang Su, Guangrun Wang, Liang Lin
2007.03213	Enabling On-Device CNN Training by Self-Supervised Instance Filtering and Error Map Pruning	Machine Learning (cs.LG)	Yawen Wu, Zhepeng Wang, Yiyu Shi, Jingtong Hu
2007.03219	Meta-Learning with Network Pruning	Machine Learning (cs.LG)	Hongduan Tian, Bo Liu, Xiao-Tong Yuan, Qingshan Liu
2007.03260	Lossless CNN Channel Pruning via Gradient Resetting and Convolutional Re-parameterization	Machine Learning (cs.LG)	Xiaohan Ding, Tianxiang Hao, Ji Liu, Jungong Han, Yuchen Guo, Guiguang Ding
2007.03903	AUSN: Approximately Uniform Quantization by Adaptively Superimposing Non-uniform Distribution for Deep Neural Networks	Signal Processing (eess.SP)	Liu Fangxin, Zhao Wenbo, Wang Yanzhi, Dai Changzhi, Jiang Li
2007.03938	Operation-Aware Soft Channel Pruning using Differentiable Masks	Machine Learning (cs.LG)	Minsoo Kang, Bohyung Han
2007.04006	Accelerated Sparse Bayesian Learning via Screening Test and Its Applications	Machine Learning (stat.ML)	Yiping Jiang, Tianshi Chen
2007.04057	Reversible Data Hiding in Encrypted Images Based on Bit plane Compression of Prediction Error	Multimedia (cs.MM)	Youqing Wu, Wenjing Ma, Yinyin Peng, Ruiling Zhang, Zhaoxia Yin
2007.04108	A Distilled Model for Tracking and Tracker Fusion	Computer Vision and Pattern Recognition (cs.CV)	Matteo Dunnhofer, Niki Martinel, Christian Micheloni
2007.04174	Robust Re-Identification by Multiple Views Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Angelo Porrello, Luca Bergamini, Simone Calderara
2007.04216	RicciNets: Curvature-guided Pruning of High-performance Neural Networks Using Ricci Flow	Machine Learning (cs.LG)	Samuel Glass, Simeon Spasov, Pietro Liò
2007.04242	Dynamic Group Convolution for Accelerating Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Zhuo Su, Linpu Fang, Wenxiong Kang, Dewen Hu, Matti Pietikäinen, Li Liu
2007.04457	Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs	Distributed, Parallel, and Cluster Computing (cs.DC)	Jieyang Chen, Lipeng Wan, Xin Liang, Ben Whitney, Qing Liu, Dave Pugmire, Nicholas Thompson, Matthew Wolf, Todd Munson, Ian Foster, Scott Klasky
2007.04756	Learning to Prune Deep Neural Networks via Reinforcement Learning	Artificial Intelligence (cs.AI)	Manas Gupta, Siddharth Aravindan, Aleksandra Kalisz, Vijay Chandrasekhar, Lin Jie
2007.05100	SGQuant: Squeezing the Last Bit on Graph Neural Networks with Specialized Quantization	Machine Learning (cs.LG)	Boyuan Feng, Yuke Wang, Xu Li, Shu Yang, Xueqiao Peng, Yufei Ding
2007.05146	Optical Flow Distillation: Towards Efficient and Stable Video Style Transfer	Computer Vision and Pattern Recognition (cs.CV)	Xinghao Chen, Yiman Zhang, Yunhe Wang, Han Shu, Chunjing Xu, Chang Xu
2007.05223	Distillation Guided Residual Learning for Binary Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Jianming Ye, Shiliang Zhang, Jingdong Wang
2007.05299	Data-Efficient Ranking Distillation for Image Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Zakaria Laskar, Juho Kannala
2007.05611	Deep Contextual Clinical Prediction with Reverse Distillation	Machine Learning (cs.LG)	Rohan S. Kodialam, Rebecca Boiarsky, David Sontag
2007.05617	Quantization in Relative Gradient Angle Domain For Building Polygon Estimation	Computer Vision and Pattern Recognition (cs.CV)	Yuhao Chen, Yifan Wu, Linlin Xu, Alexander Wong
2007.05667	To filter prune, or to layer prune, that is the question	Computer Vision and Pattern Recognition (cs.CV)	Sara Elkerdawy, Mostafa Elhoushi, Abhineet Singh, Hong Zhang, Nilanjan Ray
2007.06000	Accelerating Deep Learning Inference with Cross-Layer Data Reuse on GPUs	Distributed, Parallel, and Cluster Computing (cs.DC)	Xueying Wang, Guangli Li, Xiao Dong, Jiansong Li, Lei Liu, Xiaobing Feng
2007.06389	Term Revealing: Furthering Quantization at Run Time on Quantized DNNs	Computer Vision and Pattern Recognition (cs.CV)	H. T. Kung, Bradley McDanel, Sai Qian Zhang
2007.06483	Accelerating Translational Image Registration for HDR Images on GPU	Computer Vision and Pattern Recognition (cs.CV)	Kadir Cenk Alpay, Kadir Berkay Aydemir, Alptekin Temizel
2007.06504	Towards practical lipreading with distilled and efficient models	Computer Vision and Pattern Recognition (cs.CV)	Pingchuan Ma, Brais Martinez, Stavros Petridis, Maja Pantic
2007.06555	Adversarial robustness via robust low rank representations	Machine Learning (cs.LG)	Pranjal Awasthi, Himanshu Jain, Ankit Singh Rawat, Aravindan Vijayaraghavan
2007.06567	Lossless Compression of Structured Convolutional Models via Lifting	Machine Learning (cs.LG)	Gustav Sourek, Filip Zelezny
2007.06889	Knowledge Distillation for Multi-task Learning	Computer Vision and Pattern Recognition (cs.CV)	Wei-Hong Li, Hakan Bilen
2007.06932	REPrune: Filter Pruning via Representative Election	Computer Vision and Pattern Recognition (cs.CV)	Mincheol Park, Woojeong Kim, Suhyun Kim
2007.06963	P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection	Computer Vision and Pattern Recognition (cs.CV)	Zhiwei Zhang, Shifeng Chen, Lei Sun
2007.07075	UDBNET: Unsupervised Document Binarization Network via Adversarial Game	Computer Vision and Pattern Recognition (cs.CV)	Amandeep Kumar, Shuvozit Ghose, Pinaki Nath Chowdhury, Partha Pratim Roy, Umapada Pal
2007.07077	Unsupervised Multi-Target Domain Adaptation Through Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Le Thanh Nguyen-Meidine, Atif Bela, Madhu Kiran, Jose Dolz, Louis-Antoine Blais-Morin, Eric Granger
2007.07743	Finding Non-Uniform Quantization Schemes using Multi-Task Gaussian Processes	Computer Vision and Pattern Recognition (cs.CV)	Marcelo Gennari do Nascimento, Theo W. Costain, Victor Adrian Prisacariu
2007.07923	Image De-Quantization Using Generative Models as Priors	Computer Vision and Pattern Recognition (cs.CV)	Kalliopi Basioti, George V. Moustakides
2007.07967	Compression strategies and space-conscious representations for deep neural networks	Machine Learning (cs.LG)	Giosuè Cataldo Marinò, Gregorio Ghidoli, Marco Frasca, Dario Malchiodi
2007.08113	Defocus Blur Detection via Depth Distillation	Computer Vision and Pattern Recognition (cs.CV)	Xiaodong Cun, Chi-Man Pun
2007.08243	Lottery Tickets in Linear Models: An Analysis of Iterative Magnitude Pruning	Machine Learning (cs.LG)	Bryn Elesedy, Varun Kanade, Yee Whye Teh
2007.08301	Robust adaptive steganography based on dither modulation and modification with re-compression	Multimedia (cs.MM)	Zhaoxia Yin, Longfei Ke
2007.08386	Multi-Task Pruning for Semantic Segmentation Networks	Computer Vision and Pattern Recognition (cs.CV)	Xinghao Chen, Yunhe Wang, Yiman Zhang, Peng Du, Chunjing Xu, Chang Xu
2007.08501	Accelerating 3D Deep Learning with PyTorch3D	Computer Vision and Pattern Recognition (cs.CV)	Nikhila Ravi, Jeremy Reizenstein, David Novotny, Taylor Gordon, Wan-Yen Lo, Justin Johnson, Georgia Gkioxari
2007.08520	Accelerating Robustness Verification of Deep Neural Networks Guided by Target Labels	Machine Learning (cs.LG)	Wenjie Wan, Zhaodi Zhang, Yiwei Zhu, Min Zhang, Fu Song
2007.08954	SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression	Computation and Language (cs.CL)	Jinming Zhao, Ming Liu, Longxiang Gao, Yuan Jin, Lan Du, He Zhao, He Zhang, Gholamreza Haffari
2007.09029	Knowledge Distillation in Deep Learning and its Applications	Machine Learning (cs.LG)	Abdolmaged Alkhulaifi, Fahad Alsahli, Irfan Ahmad
2007.09625	cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data	Distributed, Parallel, and Cluster Computing (cs.DC)	Jiannan Tian, Sheng Di, Kai Zhao, Cody Rivera, Megan Hickman Fulp, Robert Underwood, Sian Jin, Xin Liang, Jon Calhoun, Dingwen Tao, Franck Cappello
2007.09785	ASAP-NMS: Accelerating Non-Maximum Suppression Using Spatially Aware Priors	Computer Vision and Pattern Recognition (cs.CV)	Rohun Tripathi, Vasu Singla, Mahyar Najibi, Bharat Singh, Abhishek Sharma, Larry Davis
2007.09867	Interpretable Foreground Object Search As Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Boren Li, Po-Yu Zhuang, Jian Gu, Mingyang Li, Ping Tan
2007.10026	Search What You Want: Barrier Panelty NAS for Mixed Precision Quantization	Computer Vision and Pattern Recognition (cs.CV)	Haibao Yu, Qi Han, Jianbo Li, Jianping Shi, Guangliang Cheng, Bin Fan
2007.10787	Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Yanning Zhou, Hao Chen, Huangjing Lin, Pheng-Ann Heng
2007.11088	Understanding BERT Rankers Under Distillation	Information Retrieval (cs.IR)	Luyu Gao, Zhuyun Dai, Jamie Callan
2007.11089	Accelerating Deep Learning Applications in Space	Computer Vision and Pattern Recognition (cs.CV)	Martina Lofqvist, José Cano
2007.11471	Geometric compression of invariant manifolds in neural nets	Machine Learning (cs.LG)	Jonas Paccolat, Leonardo Petrini, Mario Geiger, Kevin Tyloo, Matthieu Wyart
2007.11797	End-to-end Learning of Compressible Features	Computer Vision and Pattern Recognition (cs.CV)	Saurabh Singh, Sami Abu-El-Haija, Nick Johnston, Johannes Ballé, Abhinav Shrivastava, George Toderici
2007.12000	ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation	Machine Learning (cs.LG)	Fei Mi, Xiaoyu Lin, Boi Faltings
2007.12174	Recursive Variable-Length State Compression for Multi-Core Software Model Checking	Distributed, Parallel, and Cluster Computing (cs.DC)	Freark I. van der Berg
2007.12355	Dynamic Knowledge Distillation for Black-box Hypothesis Transfer Learning	Machine Learning (cs.LG)	Yiqin Yu, Xu Min, Shiwan Zhao, Jing Mei, Fei Wang, Dongsheng Li, Kenney Ng, Shaochun Li
2007.12362	Performance analysis of weighted low rank model with sparse image histograms for face recognition under lowlevel illumination and occlusion	Computer Vision and Pattern Recognition (cs.CV)	K.V. Sridhar, Raghu vamshi Hemadri
2007.12401	Predictive Information Accelerates Learning in RL	Machine Learning (cs.LG)	Kuang-Huei Lee, Ian Fischer, Anthony Liu, Yijie Guo, Honglak Lee, John Canny, Sergio Guadarrama
2007.12731	COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature	Information Retrieval (cs.IR)	Colby Wise, Vassilis N. Ioannidis, Miguel Romero Calvo, Xiang Song, George Price, Ninad Kulkarni, Ryan Brand, Parminder Bhatia, George Karypis
2007.12892	MP3 Compression To Diminish Adversarial Noise in End-to-End Speech Recognition	Audio and Speech Processing (eess.AS)	Iustina Andronic, Ludwig Kürzinger, Edgar Ricardo Chavez Rosas, Gerhard Rigoll, Bernhard U. Seeber
2007.13428	Two-Level Residual Distillation based Triple Network for Incremental Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Dongbao Yang, Yu Zhou, Dayan Wu, Can Ma, Fei Yang, Weiping Wang
2007.13552	HeAT -- a Distributed and GPU-accelerated Tensor Framework for Data Analytics	Distributed, Parallel, and Cluster Computing (cs.DC)	Markus Götz, Daniel Coquelin, Charlotte Debus, Kai Krajsek, Claudia Comito, Philipp Knechtges, Björn Hagemeier, Michael Tarnawa, Simon Hanselmann, Martin Siggel, Achim Basermann, Achim Streit
2007.14137	Nonnegative Low Rank Tensor Approximation and its Application to Multi-dimensional Images	Computer Vision and Pattern Recognition (cs.CV)	Tai-Xiang Jiang, Michael K. Ng, Junjun Pan, Guangjing Song
2007.14283	Faster Mean-shift: GPU-accelerated Embedding-clustering for Cell Segmentation and Tracking	Computer Vision and Pattern Recognition (cs.CV)	Mengyang Zhao, Aadarsh Jha, Quan Liu, Bryan A. Millis, Anita Mahadevan-Jansen, Le Lu, Bennett A. Landman, Matthew J.Tyskac, Yuankai Huo
2007.14314	On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures	Computer Vision and Pattern Recognition (cs.CV)	Matt Poyser, Amir Atapour-Abarghouei, Toby P. Breckon
2007.14374	Accelerating Federated Learning over Reliability-Agnostic Clients in Mobile Edge Computing Systems	Distributed, Parallel, and Cluster Computing (cs.DC)	Wentai Wu, Ligang He, Weiwei Lin, Rui Mao
2007.14917	Compressing Deep Neural Networks via Layer Fusion	Machine Learning (cs.LG)	James O' Neill, Greg Ver Steeg, Aram Galstyan
2008.00261	Distilling Visual Priors from Self-Supervised Learning	Computer Vision and Pattern Recognition (cs.CV)	Bingchen Zhao, Xin Wen
2008.00325	Bringing UMAP Closer to the Speed of Light with GPU Acceleration	Machine Learning (cs.LG)	Corey J. Nolet, Victor Lafargue, Edward Raff, Thejaswi Nanditale, Tim Oates, John Zedlewski, Joshua Patterson
2008.00506	Differentiable Feature Aggregation Search for Knowledge Distillation	Machine Learning (cs.LG)	Yushuo Guan, Pengyu Zhao, Bingxuan Wang, Yuanxing Zhang, Cong Yao, Kaigui Bian, Jian Tang
2008.00671	TutorNet: Towards Flexible Knowledge Distillation for End-to-End Speech Recognition	Audio and Speech Processing (eess.AS)	Ji Won Yoon, Hyeonseung Lee, Hyung Yong Kim, Won Ik Cho, Nam Soo Kim
2008.01425	PowerGossip: Practical Low-Rank Communication Compression in Decentralized Deep Learning	Machine Learning (cs.LG)	Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi
2008.01458	Prime-Aware Adaptive Distillation	Computer Vision and Pattern Recognition (cs.CV)	Youcai Zhang, Zhonghao Lan, Yuchen Dai, Fangao Zeng, Yan Bai, Jie Chang, Yichen Wei
2008.01901	Machine Learning and Feature Engineering for Predicting Pulse Status during Chest Compressions	Signal Processing (eess.SP)	Diya Sashidhar (1 and 3), Heemun Kwok (2 and 3), Jason Coult (3), Jen Blackwood (3), Peter Kudenchuck (3 and 4), Shiv Bhandari (3), Thomas Rea (3 and 5), J. Nathan Kutz (1 and 3) ((1) Department of Applied Mathematics, University of Washington (2) Department of Emergency Medicine, University of Washington, (3) Center for Progress in Resuscitation, (4) Heart Institute, University of Washington, (5) Harborview Medical Center, and General Internal Medicine, University of Washington)
2008.01989	Differentially Private Accelerated Optimization Algorithms	Machine Learning (cs.LG)	Nurdan Kuru, Ş. İlker Birbil, Mert Gurbuzbalaban, Sinan Yildirim
2008.02002	Fast top-K Cosine Similarity Search through XOR-Friendly Binary Quantization on GPUs	Computer Vision and Pattern Recognition (cs.CV)	Xiaozheng Jian, Jianqiu Lu, Zexi Yuan, Ao Li
2008.02014	Optimizing AD Pruning of Sponsored Search with Reinforcement Learning	Machine Learning (cs.LG)	Yijiang Lian, Zhijie Chen, Xin Pei, Shuang Li, Yifei Wang, Yuefeng Qiu, Zhiheng Zhang, Zhipeng Tao, Liang Yuan, Hanju Guan, Kefeng Zhang, Zhigang Li, Xiaochun Liu
2008.02093	Point Proposal Network: Accelerating Point Source Detection Through Deep Learning	Computer Vision and Pattern Recognition (cs.CV)	Duncan Tilley, Christopher W. Cleghorn, Kshitij Thorat, Roger Deane
2008.02897	Iterative Compression of End-to-End ASR Model using AutoML	Machine Learning (cs.LG)	Abhinav Mehrotra, Łukasz Dudziak, Jinsu Yeo, Young-yoon Lee, Ravichander Vipperla, Mohamed S. Abdelfattah, Sourav Bhattacharya, Samin Ishtiaq, Alberto Gil C. P. Ramos, SangJeong Lee, Daehyun Kim, Nicholas D. Lane
2008.03433	GPU-Accelerated Primal Learning for Extremely Fast Large-Scale Classification	Machine Learning (cs.LG)	John T. Halloran, David M. Rocke
2008.03789	3D Human Motion Estimation via Motion Compression and Refinement	Computer Vision and Pattern Recognition (cs.CV)	Zhengyi Luo, S. Alireza Golestaneh, Kris M. Kitani
2008.03822	Distilling the Knowledge of BERT for Sequence-to-Sequence ASR	Computation and Language (cs.CL)	Hayato Futami, Hirofumi Inaguma, Sei Ueno, Masato Mimura, Shinsuke Sakai, Tatsuya Kawahara
2008.03923	Knowledge Distillation and Data Selection for Semi-Supervised Learning in CTC Acoustic Models	Computation and Language (cs.CL)	Prakhar Swarup, Debmalya Chakrabarty, Ashtosh Sapru, Hitesh Tulsiani, Harish Arsikere, Sri Garimella
2008.05000	Degree-Quant: Quantization-Aware Training for Graph Neural Networks	Machine Learning (cs.LG)	Shyam A. Tailor, Javier Fernandez-Marques, Nicholas D. Lane
2008.05124	Leveraging Automated Mixed-Low-Precision Quantization for tiny edge microcontrollers	Machine Learning (cs.LG)	Manuele Rusci, Marco Fariselli, Alessandro Capotondi, Luca Benini
2008.05221	Compression of Deep Learning Models for Text: A Survey	Computation and Language (cs.CL)	Manish Gupta, Puneet Agrawal
2008.05441	Stable Low-rank Tensor Decomposition for Compression of Convolutional Neural Network	Computer Vision and Pattern Recognition (cs.CV)	Anh-Huy Phan, Konstantin Sobolev, Konstantin Sozykin, Dmitry Ermilov, Julia Gusak, Petr Tichavsky, Valeriy Glukhov, Ivan Oseledets, Andrzej Cichocki
2008.05672	JQF: Optimal JPEG Quantization Table Fusion by Simulated Annealing on Texture Images and Predicting Textures	Multimedia (cs.MM)	Chen-Hsiu Huang, Ja-Ling Wu
2008.05767	Weight Equalizing Shift Scaler-Coupled Post-training Quantization	Machine Learning (cs.LG)	Jihun Oh, SangJeong Lee, Meejeong Park, Pooni Walagaurav, Kiseok Kwon
2008.05969	Variance Regularization for Accelerating Stochastic Optimization	Machine Learning (cs.LG)	Tong Yang, Long Sha, Pengyu Hong
2008.06180	Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data	Distributed, Parallel, and Cluster Computing (cs.DC)	Sohei Itahara, Takayuki Nishio, Yusuke Koda, Masahiro Morikura, Koji Yamamoto
2008.06388	Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review	Machine Learning (cs.LG)	Michael Roberts, Derek Driggs, Matthew Thorpe, Julian Gilbey, Michael Yeung, Stephan Ursprung, Angelica I. Aviles-Rivero, Christian Etmann, Cathal McCague, Lucian Beer, Jonathan R. Weir-McCall, Zhongzhao Teng, James H.F. Rudd, Evis Sala, Carola-Bibiane Schönlieb (on behalf of the AIX-COVNET collaboration)
2008.06653	Evaluating Lossy Compression Rates of Deep Generative Models	Machine Learning (cs.LG)	Sicong Huang, Alireza Makhzani, Yanshuai Cao, Roger Grosse
2008.06814	Cascaded channel pruning using hierarchical self-distillation	Computer Vision and Pattern Recognition (cs.CV)	Roy Miles, Krystian Mikolajczyk
2008.06867	Audio Dequantization for High Fidelity Audio Generation in Flow-based Neural Vocoder	Audio and Speech Processing (eess.AS)	Hyun-Wook Yoon, Sang-Hoon Lee, Hyeong-Rae Noh, Seong-Whan Lee
2008.07063	To Bag is to Prune	Machine Learning (stat.ML)	Philippe Goulet Coulombe
2008.07112	AnciNet: An Efficient Deep Learning Approach for Feedback Compression of Estimated CSI in Massive MIMO Systems	Signal Processing (eess.SP)	Yuyao Sun, Wei Xu, Lisheng Fan, Geoffrey Ye Li, George K. Karagiannidis
2008.07130	Reversing the cycle: self-supervised deep stereo through enhanced monocular distillation	Computer Vision and Pattern Recognition (cs.CV)	Filippo Aleotti, Fabio Tosi, Li Zhang, Matteo Poggi, Stefano Mattoccia
2008.07816	Knowledge Transfer via Dense Cross-Layer Mutual-Distillation	Computer Vision and Pattern Recognition (cs.CV)	Anbang Yao, Dawei Sun
2008.07948	Adaptive Distillation for Decentralized Learning from Heterogeneous Clients	Machine Learning (cs.LG)	Jiaxin Ma, Ryo Yonetani, Zahid Iqbal
2008.08284	Channel-wise Hessian Aware trace-Weighted Quantization of Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Xu Qian, Victor Li, Crews Darren
2008.08289	Restructuring, Pruning, and Adjustment of Deep Models for Parallel Distributed Inference	Machine Learning (cs.LG)	Afshin Abdi, Saeed Rashidi, Faramarz Fekri, Tushar Krishna
2008.08316	Data-Independent Structured Pruning of Neural Networks via Coresets	Machine Learning (cs.LG)	Ben Mussay, Daniel Feldman, Samson Zhou, Vladimir Braverman, Margarita Osadchy
2008.09072	Utilizing Explainable AI for Quantization and Pruning of Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Muhammad Sabih, Frank Hannig, Juergen Teich
2008.09206	Training of mixed-signal optical convolutional neural network with reduced quantization level	Signal Processing (eess.SP)	Joseph Ulseth, Zheyuan Zhu, Guifang Li, Shuo Pang
2008.09342	Kronecker CP Decomposition with Fast Multiplication for Compressing RNNs	Computer Vision and Pattern Recognition (cs.CV)	Dingheng Wang, Bijiao Wu, Guangshe Zhao, Hengnu Chen, Lei Deng, Tianyi Yan, Guoqi Li
2008.09457	DOPE: Distillation Of Part Experts for whole-body 3D pose estimation in the wild	Computer Vision and Pattern Recognition (cs.CV)	Philippe Weinzaepfel, Romain Brégier, Hadrien Combaluzier, Vincent Leroy, Grégory Rogez
2008.09903	iCVI-ARTMAP: Accelerating and improving clustering using adaptive resonance theory predictive mapping and incremental cluster validity indices	Machine Learning (cs.LG)	Leonardo Enzo Brito da Silva, Nagasharath Rayapati, Donald C. Wunsch II
2008.09958	Matching Guided Distillation	Computer Vision and Pattern Recognition (cs.CV)	Kaiyu Yue, Jiangfan Deng, Feng Zhou
2008.10092	Adaptive Subband Compression of Streaming Data for Power System Monitoring and Control	Signal Processing (eess.SP)	Xinyi Wang, Yilu Liu, Lang Tong
2008.10191	Affinity-aware Compression and Expansion Network for Human Parsing	Computer Vision and Pattern Recognition (cs.CV)	Xinyan Zhang, Yunfeng Wang, Pengfei Xiong
2008.10850	Discriminability Distillation in Group Representation Learning	Computer Vision and Pattern Recognition (cs.CV)	Manyuan Zhang, Guanglu Song, Hang Zhou, Yu Liu
2008.11062	GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework	Machine Learning (cs.LG)	Haotao Wang, Shupeng Gui, Haichuan Yang, Ji Liu, Zhangyang Wang
2008.11281	Accelerating Federated Learning in Heterogeneous Data and Computational Environments	Machine Learning (cs.LG)	Dimitris Stripelis, Jose Luis Ambite
2008.11420	Low Complexity Trellis-Coded Quantization in Versatile Video Coding	Multimedia (cs.MM)	Meng Wang, Shiqi Wang, Junru Li, Li Zhang, Yue Wang, Siwei Ma, Sam Kwong
2008.11827	Smart-PGSim: Using Neural Network to Accelerate AC-OPF Power Grid Simulation	Signal Processing (eess.SP)	Wenqian Dong, Zhen Xie, Gokcen Kestor, Dong Li
2008.11832	Adaptive Neural Network-Based Approximation to Accelerate Eulerian Fluid Simulation	Machine Learning (cs.LG)	Wenqian Dong, Jie Liu, Zhen Xie, Dong Li
2008.11849	SparseRT: Accelerating Unstructured Sparsity on GPUs for Deep Learning Inference	Machine Learning (cs.LG)	Ziheng Wang
2008.11911	Domain Adaptation Through Task Distillation	Computer Vision and Pattern Recognition (cs.CV)	Brady Zhou, Nimit Kalra, Philipp Krähenbühl
2008.12094	MetaDistiller: Network Self-Boosting via Meta-Learned Top-Down Distillation	Computer Vision and Pattern Recognition (cs.CV)	Benlin Liu, Yongming Rao, Jiwen Lu, Jie Zhou, Cho-jui Hsieh
2008.12889	Source-Aware Neural Speech Coding for Noisy Speech Compression	Audio and Speech Processing (eess.AS)	Haici Yang, Seungkwon Beack, Minje Kim
2008.13128	Optimal Quantization for Batch Normalization in Neural Network Deployments and Beyond	Machine Learning (cs.LG)	Dachao Lin, Peiqin Sun, Guangzeng Xie, Shuchang Zhou, Zhihua Zhang
2008.13485	ROS-Neuro Integration of Deep Convolutional Autoencoders for EEG Signal Compression in Real-time BCIs	Machine Learning (cs.LG)	Andrea Valenti, Michele Barsotti, Raffaello Brondi, Davide Bacciu, Luca Ascari
2008.13528	Microsoft Recommenders: Tools to Accelerate Developing Recommender Systems	Information Retrieval (cs.IR)	Scott Graham, Jun-Ki Min, Tao Wu
2008.13578	MCMIA: Model Compression Against Membership Inference Attack in Deep Neural Networks	Machine Learning (cs.LG)	Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran
2008.13590	Efficient and Sparse Neural Networks by Pruning Weights in a Multiobjective Learning Approach	Machine Learning (cs.LG)	Malena Reiners, Kathrin Klamroth, Michael Stiglmayr
2009.00189	Object Detection-Based Variable Quantization Processing	Computer Vision and Pattern Recognition (cs.CV)	Likun Liu, Hua Qi
2009.00210	Semantics-aware Adaptive Knowledge Distillation for Sensor-to-Vision Action Recognition	Computer Vision and Pattern Recognition (cs.CV)	Yang Liu, Guanbin Li, Liang Lin
2009.00694	Automatic Assignment of Radiology Examination Protocols Using Pre-trained Language Models with Knowledge Distillation	Computation and Language (cs.CL)	Wilson Lau, Laura Aaltonen, Martin Gunn, Meliha Yetisgen
2009.01174	Transform Quantization for CNN Compression	Computer Vision and Pattern Recognition (cs.CV)	Sean I. Young, Wang Zhe, David Taubman, Bernd Girod
2009.01395	A Partial Regularization Method for Network Compression	Machine Learning (cs.LG)	E Zhenqian, Gao Weiguo
2009.01759	Intra-Utterance Similarity Preserving Knowledge Distillation for Audio Tagging	Audio and Speech Processing (eess.AS)	Chun-Chieh Chang, Chieh-Chi Kao, Ming Sun, Chao Wang
2009.01956	Compression-aware Continual Learning using Singular Value Decomposition	Computer Vision and Pattern Recognition (cs.CV)	Varigonda Pavan Teja, Priyadarshini Panda
2009.01974	FedDistill: Making Bayesian Model Ensemble Applicable to Federated Learning	Machine Learning (cs.LG)	Hong-You Chen, Wei-Lun Chao
2009.02326	CLEANN: Accelerated Trojan Shield for Embedded Neural Networks	Machine Learning (cs.LG)	Mojan Javaheripi, Mohammad Samragh, Gregory Fields, Tara Javidi, Farinaz Koushanfar
2009.02388	On Communication Compression for Distributed Optimization on Heterogeneous Data	Machine Learning (cs.LG)	Sebastian U. Stich
2009.03294	GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training	Machine Learning (cs.LG)	Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-yan Liu, Liwei Wang
2009.03998	Tangent Space Based Alternating Projections for Nonnegative Low Rank Matrix Approximation	Machine Learning (cs.LG)	Guangjing Song, Michael K. Ng, Tai-Xiang Jiang
2009.04120	On the Orthogonality of Knowledge Distillation with Other Techniques: From an Ensemble Perspective	Machine Learning (cs.LG)	SeongUk Park, KiYoon Yoo, Nojun Kwak
2009.04126	FleXOR: Trainable Fractional Quantization	Machine Learning (cs.LG)	Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Yongkweon Jeon, Baeseong Park, Jeongin Yun
2009.04619	Accelerating High-Order Stencils on GPUs	Distributed, Parallel, and Cluster Computing (cs.DC)	Ryuichi Sai, John Mellor-Crummey, Xiaozhu Meng, Mauricio Araya-Polo, Jie Meng
2009.04646	Key-Point Sequence Lossless Compression for Intelligent Video Analysis	Multimedia (cs.MM)	Weiyao Lin, Xiaoyi He, Wenrui Dai, John See, Tushar Shinde, Hongkai Xiong, Lingyu Duan
2009.05014	OrthoReg: Robust Network Pruning Using Orthonormality Regularization	Computer Vision and Pattern Recognition (cs.CV)	Ekdeep Singh Lubana, Puja Trivedi, Conrad Hougen, Robert P. Dick, Alfred O. Hero
2009.05167	Accelerating Real-Time Question Answering via Question Generation	Computation and Language (cs.CL)	Yuwei Fang, Shuohang Wang, Zhe Gan, Siqi Sun, Jingjing Liu
2009.05226	Extending Label Smoothing Regularization with Self-Knowledge Distillation	Machine Learning (cs.LG)	Ji-Yue Wang, Pei Zhang, Wen-feng Pang, Jie Li
2009.05252	Novel and Effective CNN-Based Binarization for Historically Degraded As-built Drawing Maps	Computer Vision and Pattern Recognition (cs.CV)	Kuo-Liang Chung, De-Wei Hsieh
2009.05300	Enabling Image Recognition on Constrained Devices Using Neural Network Pruning and a CycleGAN	Computer Vision and Pattern Recognition (cs.CV)	August Lidfelt, Daniel Isaksson, Ludwig Hedlund, Simon Åberg, Markus Borg, Erik Larsson
2009.05697	YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design	Computer Vision and Pattern Recognition (cs.CV)	Yuxuan Cai, Hongjia Li, Geng Yuan, Wei Niu, Yanyu Li, Xulong Tang, Bin Ren, Yanzhi Wang
2009.05972	SSKD: Self-Supervised Knowledge Distillation for Cross Domain Adaptive Person Re-Identification	Computer Vision and Pattern Recognition (cs.CV)	Junhui Yin, Jiayan Qiu, Siqing Zhang, Zhanyu Ma, Jun Guo
2009.05982	Improving Deep Video Compression by Resolution-adaptive Flow Coding	Computer Vision and Pattern Recognition (cs.CV)	Zhihao Hu (1), Zhenghao Chen (2), Dong Xu (2), Guo Lu (3), Wanli Ouyang (2), Shuhang Gu (2) ((1) College of Software, Beihang University, China, (2) School of Electrical and Information Engineering, The University of Sydney, Australia, (3) School of Computer Science & Technology, Beijing Institute of Technology, China)
2009.06116	Accelerating COVID-19 Differential Diagnosis with Explainable Ultrasound Image Analysis	Computer Vision and Pattern Recognition (cs.CV)	Jannis Born, Nina Wiedemann, Gabriel Brändle, Charlotte Buhre, Bastian Rieck, Karsten Borgwardt
2009.06245	Accelerating gradient-based topology optimization design with dual-model neural networks	Artificial Intelligence (cs.AI)	Chao Qian, Wenjing Ye
2009.06902	Collaborative Distillation in the Parameter and Spectrum Domains for Video Action Recognition	Computer Vision and Pattern Recognition (cs.CV)	Haisheng Su, Jing Su, Dongliang Wang, Weihao Gan, Wei Wu, Mengmeng Wang, Junjie Yan, Yu Qiao
2009.07032	Noisy Self-Knowledge Distillation for Text Summarization	Computation and Language (cs.CL)	Yang Liu, Sheng Shen, Mirella Lapata
2009.07253	Autoregressive Knowledge Distillation through Imitation Learning	Computation and Language (cs.CL)	Alexander Lin, Jeremy Wohlwend, Howard Chen, Tao Lei
2009.07325	GPU Accelerated RIS-based Influence Maximization Algorithm	Distributed, Parallel, and Cluster Computing (cs.DC)	Soheil Shahrouz, Saber Salehkaleybar, Matin Hashemi
2009.07411	Mimic and Conquer: Heterogeneous Tree Structure Distillation for Syntactic NLP	Computation and Language (cs.CL)	Hao Fei, Yafeng Ren, Donghong Ji
2009.07453	Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation	Machine Learning (cs.LG)	Insoo Chung, Byeongwook Kim, Yoonjung Choi, Se Jung Kwon, Yongkweon Jeon, Baeseong Park, Sangha Kim, Dongsoo Lee
2009.07531	Simplified TinyBERT: Knowledge Distillation for Document Retrieval	Information Retrieval (cs.IR)	Xuanang Chen, Ben He, Kai Hui, Le Sun, Yingfei Sun
2009.07604	Compressing Facial Makeup Transfer Networks by Collaborative Distillation and Kernel Decomposition	Computer Vision and Pattern Recognition (cs.CV)	Bianjiang Yang, Zi Hui, Haoji Hu, Xinyi Hu, Lu Yu
2009.07785	Accelerating Domain Propagation: an Efficient GPU-Parallel Algorithm over Sparse Matrices	Distributed, Parallel, and Cluster Computing (cs.DC)	Boro Sofranac, Ambros Gleixner, Sebastian Pokutta
2009.07823	GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network	Computer Vision and Pattern Recognition (cs.CV)	Prune Truong, Martin Danelljan, Luc Van Gool, Radu Timofte
2009.07999	Distilled One-Shot Federated Learning	Machine Learning (cs.LG)	Yanlin Zhou, George Pu, Xiyao Ma, Xiaolin Li, Dapeng Wu
2009.08169	Holistic Filter Pruning for Efficient Deep Neural Networks	Machine Learning (cs.LG)	Lukas Enderich, Fabian Timm, Wolfram Burgard
2009.08278	Accelerated solving of coupled, non-linear ODEs through LSTM-AI	Machine Learning (cs.LG)	Camila Faccini de Lima, Juliano Ferrari Gianlupi, John Metzcar, Juliette Zerick
2009.08348	S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning	Computer Vision and Pattern Recognition (cs.CV)	Karsten Roth, Timo Milbich, Björn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi
2009.08576	Pruning Neural Networks at Initialization: Why are We Missing the Mark?	Machine Learning (cs.LG)	Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin
2009.08591	Accelerating Search on Binary Codes in Weighted Hamming Space	Computer Vision and Pattern Recognition (cs.CV)	Zhenyu Weng, Yuesheng Zhu, Ruixin Liu
2009.08716	Federated Learning with Nesterov Accelerated Gradient Momentum Method	Machine Learning (cs.LG)	Zhengjie Yang, Wei Bao, Dong Yuan, Nguyen H. Tran, Albert Y. Zomaya
2009.08825	Densely Guided Knowledge Distillation using Multiple Teacher Assistants	Computer Vision and Pattern Recognition (cs.CV)	Wonchul Son, Jaemin Na, Wonjun Hwang
2009.09140	Introspective Learning by Distilling Knowledge from Online Self-explanation	Computer Vision and Pattern Recognition (cs.CV)	Jindong Gu, Zhiliang Wu, Volker Tresp
2009.09152	Weight Distillation: Transferring the Knowledge in Neural Network Parameters	Computation and Language (cs.CL)	Ye Lin, Yanyang Li, Ziyang Wang, Bei Li, Quan Du, Tong Xiao, Jingbo Zhu
2009.09402	Accelerating Auxiliary Function-based Independent Vector Analysis	Audio and Speech Processing (eess.AS)	Andreas Brendel, Walter Kellermann
2009.09427	Dialogue Distillation: Open-domain Dialogue Augmentation Using Unpaired Data	Computation and Language (cs.CL)	Rongsheng Zhang, Yinhe Zheng, Jianzhi Shao, Xiaoxi Mao, Yadong Xi, Minlie Huang
2009.09724	Conditional Automated Channel Pruning for Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Yixin Liu, Yong Guo, Zichang Liu, Haohua Liu, Jingjie Zhang, Zejun Chen, Jing Liu, Jian Chen
2009.09922	Feature Distillation With Guided Adversarial Contrastive Learning	Machine Learning (cs.LG)	Tao Bai, Jinnan Chen, Jun Zhao, Bihan Wen, Xudong Jiang, Alex Kot
2009.09936	Prune Responsibly	Computer Vision and Pattern Recognition (cs.CV)	Michela Paganini
2009.09940	CNNPruner: Pruning Convolutional Neural Networks with Visual Analytics	Computer Vision and Pattern Recognition (cs.CV)	Guan Li, Junpeng Wang, Han-Wei Shen, Kaixin Chen, Guihua Shan, Zhonghua Lu
2009.10115	Extreme compression of grayscale images	Computer Vision and Pattern Recognition (cs.CV)	Franklin Mendivil, Örjan Stenflo
2009.10893	Pruning Convolutional Filters using Batch Bridgeout	Machine Learning (cs.LG)	Najeeb Khan, Ian Stavness
2009.11094	Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot	Machine Learning (cs.LG)	Jingtong Su, Yihang Chen, Tianle Cai, Tianhao Wu, Ruiqi Gao, Liwei Wang, Jason D. Lee
2009.11839	A Gradient Flow Framework For Analyzing Network Pruning	Machine Learning (cs.LG)	Ekdeep Singh Lubana, Robert P. Dick
2009.11859	Multi-Frame to Single-Frame: Knowledge Distillation for 3D Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Yue Wang, Alireza Fathi, Jiajun Wu, Thomas Funkhouser, Justin Solomon
2009.11896	Bootstrapped Q-learning with Context Relevant Observation Pruning to Generalize in Text-based Games	Machine Learning (cs.LG)	Subhajit Chaudhury, Daiki Kimura, Kartik Talamadupula, Michiaki Tatsubori, Asim Munawar, Ryuki Tachibana
2009.12812	TernaryBERT: Distillation-aware Ultra-low Bit BERT	Computation and Language (cs.CL)	Wei Zhang, Lu Hou, Yichun Yin, Lifeng Shang, Xiao Chen, Xin Jiang, Qun Liu
2009.13044	Kernel Based Progressive Distillation for Adder Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Yixing Xu, Chang Xu, Xinghao Chen, Wei Zhang, Chunjing Xu, Yunhe Wang
2009.13062	Accelerating Multi-Model Inference by Merging DNNs of Different Weights	Machine Learning (cs.LG)	Joo Seong Jeong, Soojeong Kim, Gyeong-In Yu, Yunseong Lee, Byung-Gon Chun
2009.13101	Distillation of Weighted Automata from Recurrent Neural Networks using a Spectral Approach	Machine Learning (cs.LG)	Remi Eyraud, Stephane Ayache
2009.13829	TinyGAN: Distilling BigGAN for Conditional Image Generation	Computer Vision and Pattern Recognition (cs.CV)	Ting-Yun Chang, Chi-Jen Lu
2009.14167	Contrastive Distillation on Intermediate Representations for Language Model Compression	Computation and Language (cs.CL)	Siqi Sun, Zhe Gan, Yu Cheng, Yuwei Fang, Shuohang Wang, Jingjing Liu
2009.14244	Acceleration of Large Margin Metric Learning for Nearest Neighbor Classification Using Triplet Mining and Stratified Sampling	Machine Learning (cs.LG)	Parisa Abdolrahim Poorheravi, Benyamin Ghojogh, Vincent Gaudet, Fakhri Karray, Mark Crowley
2009.14410	Pruning Filter in Filter	Computer Vision and Pattern Recognition (cs.CV)	Fanxu Meng, Hao Cheng, Ke Li, Huixiang Luo, Xiaowei Guo, Guangming Lu, Xing Sun
2009.14416	Efficient Kernel Transfer in Knowledge Distillation	Machine Learning (cs.LG)	Qi Qian, Hao Li, Juhua Hu
2009.14502	Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks	Machine Learning (cs.LG)	Yoonho Boo, Sungho Shin, Jungwook Choi, Wonyong Sung
2009.14822	Pea-KD: Parameter-efficient and Accurate Knowledge Distillation	Machine Learning (cs.LG)	Ikhyun Cho, U Kang
2010.00071	Erratum Concerning the Obfuscated Gradients Attack on Stochastic Activation Pruning	Machine Learning (cs.LG)	Guneet S. Dhillon, Nicholas Carlini
2010.00195	BiLiMO: Bit-Limited MIMO Radar via Task-Based Quantization	Signal Processing (eess.SP)	Feng Xi, Nir Shlezinger, Yonina C. Eldar
2010.00363	How LSTM Encodes Syntax: Exploring Context Vectors and Semi-Quantization on Natural Text	Computation and Language (cs.CL)	Chihiro Shibata, Kei Uchiumi, Daichi Mochihashi
2010.00520	On the Compression of Translation Operator Tensors in FMM-FFT-Accelerated SIE Simulators via Tensor Decompositions	Signal Processing (eess.SP)	Cheng Qian, Abdulkadir C. Yucel
2010.00769	Supervised Heart Rate Tracking using Wrist-Type Photoplethysmographic (PPG) Signals during Physical Exercise without Simultaneous Acceleration Signals	Signal Processing (eess.SP)	Mahmoud Essalat, Mahdi Boloursaz Mashhadi, Farokh Marvasti
2010.00795	Online Knowledge Distillation via Multi-branch Diversity Enhancement	Computer Vision and Pattern Recognition (cs.CV)	Zheng Li, Ying Huang, Defang Chen, Tianren Luo, Ning Cai, Zhigeng Pan
2010.01084	Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction	Machine Learning (stat.ML)	Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang
2010.01189	Neighbourhood Distillation: On the benefits of non end-to-end distillation	Machine Learning (cs.LG)	Laëtitia Shao, Max Moroz, Elad Eban, Yair Movshovitz-Attias
2010.01242	Nonconvex Regularization for Network Slimming:Compressing CNNs Even More	Computer Vision and Pattern Recognition (cs.CV)	Kevin Bui, Fredrick Park, Shuai Zhang, Yingyong Qi, Jack Xin
2010.01251	UCP: Uniform Channel Pruning for Deep Convolutional Neural Networks Compression and Acceleration	Computer Vision and Pattern Recognition (cs.CV)	Jingfei Chang, Yang Lu, Ping Xue, Xing Wei, Zhen Wei
2010.01343	A Variational Information Bottleneck Based Method to Compress Sequential Networks for Human Action Recognition	Computer Vision and Pattern Recognition (cs.CV)	Ayush Srivastava, Oshin Dutta, Prathosh AP, Sumeet Agarwal, Jigyasa Gupta
2010.01618	Provable Acceleration of Neural Net Training via Polyak's Momentum	Machine Learning (cs.LG)	Jun-Kun Wang, Jacob Abernethy
2010.01637	Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron	Machine Learning (cs.LG)	Jun-Kun Wang, Jacob Abernethy
2010.01791	Pruning Redundant Mappings in Transformer Models via Spectral-Normalized Identity Prior	Computation and Language (cs.CL)	Zi Lin, Jeremiah Zhe Liu, Zi Yang, Nan Hua, Dan Roth
2010.01892	Joint Pruning & Quantization for Extremely Sparse Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Po-Hsiang Yu, Sih-Sian Wu, Jan P. Klopp, Liang-Gee Chen, Shao-Yi Chien
2010.02123	Lifelong Language Knowledge Distillation	Computation and Language (cs.CL)	Yung-Sung Chuang, Shang-Yu Su, Yun-Nung Chen
2010.02377	Improving Neural Topic Models using Knowledge Distillation	Computation and Language (cs.CL)	Alexander Hoyle, Pranav Goel, Philip Resnik
2010.02488	RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs	Computer Vision and Pattern Recognition (cs.CV)	Zhiwei Xu, Thalaiyasingam Ajanthan, Vibhav Vineet, Richard Hartley
2010.02623	Comprehensive Online Network Pruning via Learnable Scaling Factors	Computer Vision and Pattern Recognition (cs.CV)	Muhammad Umair Haider, Murtaza Taj
2010.02666	Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation	Information Retrieval (cs.IR)	Sebastian Hofstätter, Sophia Althammer, Michael Schröder, Mete Sertkan, Allan Hanbury
2010.02700	Joint Collaboration and Compression Design for Distributed Sequential Estimation in a Wireless Sensor Network	Signal Processing (eess.SP)	Xiancheng Cheng, Prashant Khanduri, Boxiao Chen, Pramod K.Varshney
2010.02778	Compressing Deep Convolutional Neural Networks by Stacking Low-dimensional Binary Convolution Filters	Computer Vision and Pattern Recognition (cs.CV)	Weichao Lan, Liang Lan
2010.02838	A Closer Look at Codistillation for Distributed Training	Machine Learning (cs.LG)	Shagun Sodhani, Olivier Delalleau, Mahmoud Assran, Koustuv Sinha, Nicolas Ballas, Michael Rabbat
2010.02840	Semantic Evaluation for Text-to-SQL with Distilled Test Suites	Computation and Language (cs.CL)	Ruiqi Zhong, Tao Yu, Dan Klein
2010.03034	Why Skip If You Can Combine: A Simple Knowledge Distillation Technique for Intermediate Layers	Computation and Language (cs.CL)	Yimeng Wu, Peyman Passban, Mehdi Rezagholizade, Qun Liu
2010.03099	DiPair: Fast and Accurate Distillation for Trillion-Scale Text Matching and Pair Modeling	Computation and Language (cs.CL)	Jiecao Chen, Liu Yang, Karthik Raman, Michael Bendersky, Jung-Jung Yeh, Yun Zhou, Marc Najork, Danyang Cai, Ehsan Emadzadeh
2010.03193	Rank and run-time aware compression of NLP Applications	Computation and Language (cs.CL)	Urmish Thakker, Jesse Beu, Dibakar Gope, Ganesh Dasika, Matthew Mattina
2010.03246	Optimal Gradient Compression for Distributed and Federated Learning	Machine Learning (cs.LG)	Alyazeed Albasyoni, Mher Safaryan, Laurent Condat, Peter Richtárik
2010.03322	Training GANs with predictive projection centripetal acceleration	Machine Learning (stat.ML)	Li Keke, Zhang Ke, Liu Qiang, Yang Xinmin
2010.03954	A Survey on Deep Neural Network Compression: Challenges, Overview, and Solutions	Machine Learning (cs.LG)	Rahul Mishra, Hari Prabhat Gupta, Tanima Dutta
2010.04004	Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks	Machine Learning (cs.LG)	Ranjan Anantharaman, Yingbo Ma, Shashi Gowda, Chris Laughman, Viral Shah, Alan Edelman, Chris Rackauckas
2010.04351	Connection Pruning for Deep Spiking Neural Networks with On-Chip Learning	Neural and Evolutionary Computing (cs.NE)	Thao N.N. Nguyen, Bharadwaj Veeravalli, Xuanyao Fong
2010.04786	Reparametrizing gradient descent	Machine Learning (cs.LG)	David Sprunger
2010.04812	Locally Linear Region Knowledge Distillation	Machine Learning (cs.LG)	Xiang Deng, Zhongfei (Mark)Zhang
2010.04842	Conformal retrofitting via Riemannian manifolds: distilling task-specific graphs into pretrained embeddings	Machine Learning (cs.LG)	Justin Dieter, Arun Tejasvi Chaganty
2010.04879	Accelerate Your CNN from Three Dimensions: A Comprehensive Pruning Framework	Computer Vision and Pattern Recognition (cs.CV)	Wenxiao Wang, Minghao Chen, Shuai Zhao, Jinming Hu, Boxi Wu, Zhengxu Yu, Deng Cai, Haifeng Liu
2010.04883	Adversarial Self-Supervised Data-Free Distillation for Text Classification	Computation and Language (cs.CL)	Xinyin Ma, Yongliang Shen, Gongfan Fang, Chen Chen, Chenghao Jia, Weiming Lu
2010.04974	Distilling a Deep Neural Network into a Takagi-Sugeno-Kang Fuzzy Inference System	Artificial Intelligence (cs.AI)	Xiangming Gu, Xiang Cheng
2010.05002	Compressing Transformer-Based Semantic Parsing Models using Compositional Code Embeddings	Computation and Language (cs.CL)	Prafull Prakash, Saurabh Kumar Shashidhar, Wenlong Zhao, Subendhu Rongali, Haidar Khan, Michael Kayser
2010.05010	Structural Knowledge Distillation	Computation and Language (cs.CL)	Xinyu Wang, Yong Jiang, Zhaohui Yan, Zixia Jia, Nguyen Bach, Tao Wang, Zhongqiang Huang, Fei Huang, Kewei Tu
2010.05119	Anomaly Detection based on Zero-Shot Outlier Synthesis and Hierarchical Feature Distillation	Computer Vision and Pattern Recognition (cs.CV)	Adín Ramírez Rivera, Adil Khan, Imad E. I. Bekkouch, Taimoor S. Sheikh
2010.05265	Unsupervised Distillation of Syntactic Information from Contextualized Word Representations	Computation and Language (cs.CL)	Shauli Ravfogel, Yanai Elazar, Jacob Goldberger, Yoav Goldberg
2010.05371	Early Abandoning PrunedDTW and its application to similarity search	Machine Learning (cs.LG)	Matthieu Herrmann, Geoffrey I. Webb
2010.05445	Collective Wisdom: Improving Low-resource Neural Machine Translation using Adaptive Knowledge Distillation	Computation and Language (cs.CL)	Fahimeh Saleh, Wray Buntine, Gholamreza Haffari
2010.05448	securePrune:Secure block pruning in UTXO based blockchains using Accumulators	Distributed, Parallel, and Cluster Computing (cs.DC)	Swaroopa Reddy B
2010.06084	Accelerating the Development of Multimodal, Integrative-AI Systems with Platform for Situated Intelligence	Artificial Intelligence (cs.AI)	Sean Andrist, Dan Bohus
2010.06133	BERT-EMD: Many-to-Many Layer Mapping for BERT Compression with Earth Mover's Distance	Computation and Language (cs.CL)	Jianquan Li, Xiaokang Liu, Honghong Zhao, Ruifeng Xu, Min Yang, Yaohong Jin
2010.06715	Random Network Distillation as a Diversity Metric for Both Image and Text Generation	Machine Learning (cs.LG)	Liam Fowl, Micah Goldblum, Arjun Gupta, Amr Sharaf, Tom Goldstein
2010.06721	Ensemble Distillation for Structured Prediction: Calibrated, Accurate, Fast---Choose Three	Machine Learning (cs.LG)	Steven Reich, David Mueller, Nicholas Andrews
2010.06821	Towards Optimal Filter Pruning with Balanced Performance and Pruning Speed	Computer Vision and Pattern Recognition (cs.CV)	Dong Li, Sitong Chen, Xudong Liu, Yunda Sun, Li Zhang
2010.06993	Weight Squeezing: Reparameterization for Compression and Fast Inference	Machine Learning (cs.LG)	Artem Chumachenko, Daniil Gavrilov, Pavel Kalaidin
2010.07004	Binarization Methods for Motor-Imagery Brain-Computer Interface Classification	Signal Processing (eess.SP)	Michael Hersche, Luca Benini, Abbas Rahimi
2010.07109	An Investigation on Different Underlying Quantization Schemes for Pre-trained Language Models	Computation and Language (cs.CL)	Zihan Zhao, Yuncong Liu, Lu Chen, Qi Liu, Rao Ma, Kai Yu
2010.07152	Multi-teacher Knowledge Distillation for Knowledge Graph Completion	Artificial Intelligence (cs.AI)	Kai Wang, Yu Liu, Qian Ma, Quan Z. Sheng
2010.07334	Towards Accurate Quantization and Pruning via Data-free Knowledge Transfer	Machine Learning (cs.LG)	Chen Zhu, Zheng Xu, Ali Shafahi, Manli Shu, Amin Ghiasi, Tom Goldstein
2010.07382	Learning, compression, and leakage: Minimizing classification error via meta-universal compression principles	Machine Learning (cs.LG)	Fernando E. Rosas, Pedro A.M. Mediano, Michael Gastpar
2010.07422	Rapid Robust Principal Component Analysis: CUR Accelerated Inexact Low Rank Estimation	Machine Learning (stat.ML)	HanQin Cai, Keaton Hamm, Longxiu Huang, Jiaqi Li, Tao Wang
2010.07611	A Deeper Look at the Layerwise Sparsity of Magnitude-based Pruning	Machine Learning (cs.LG)	Jaeho Lee, Sejun Park, Sangwoo Mo, Sungsoo Ahn, Jinwoo Shin
2010.08038	Why Layer-Wise Learning is Hard to Scale-up and a Possible Solution via Accelerated Downsampling	Computer Vision and Pattern Recognition (cs.CV)	Wenchi Ma, Miao Yu, Kaidong Li, Guanghui Wang
2010.08390	Volumetric Calculation of Quantization Error in 3-D Vision Systems	Computer Vision and Pattern Recognition (cs.CV)	Eleni Bohacek, Andrew J. Coates, David R. Selviah
2010.08655	Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data	Machine Learning (cs.LG)	Mao Ye, Dhruv Choudhary, Jiecao Yu, Ellie Wen, Zeliang Chen, Jiyan Yang, Jongsoo Park, Qiang Liu, Arun Kejariwal
2010.08919	Boosting High-Level Vision with Joint Compression Artifacts Reduction and Super-Resolution	Computer Vision and Pattern Recognition (cs.CV)	Xiaoyu Xiang, Qian Lin, Jan P. Allebach
2010.08923	Towards Data Distillation for End-to-end Spoken Conversational Question Answering	Computation and Language (cs.CL)	Chenyu You, Nuo Chen, Fenglin Liu, Dongchao Yang, Yuexian Zou
2010.09336	Causal Discovery using Compression-Complexity Measures	Machine Learning (cs.LG)	Pranay SY, Nithin Nagaraj
2010.09465	A Nesterov's Accelerated quasi-Newton method for Global Routing using Deep Reinforcement Learning	Machine Learning (cs.LG)	S. Indrapriyadarsini, Shahrzad Mahboubi, Hiroshi Ninomiya, Takeshi Kamio, Hideki Asai
2010.09498	Softer Pruning, Incremental Regularization	Computer Vision and Pattern Recognition (cs.CV)	Linhang Cai, Zhulin An, Chuanguang Yang, Yongjun Xu
2010.09839	New Properties of the Data Distillation Method When Working With Tabular Data	Machine Learning (cs.LG)	Dmitry Medvedev, Alexander D'yakonov
2010.09923	Anti-Distillation: Improving reproducibility of deep networks	Machine Learning (cs.LG)	Gil I. Shamir, Lorenzo Coviello
2010.10027	Fast Video Salient Object Detection via Spatiotemporal Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Tang Yi, Li Yuan
2010.10090	Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher	Machine Learning (cs.LG)	Guangda Ji, Zhanxing Zhu
2010.10103	Two-Stage Generative Adversarial Networks for Document Image Binarization with Color Noise and Background Removal	Computer Vision and Pattern Recognition (cs.CV)	Sungho Suh, Jihun Kim, Paul Lukowicz, Yong Oh Lee
2010.10338	Asynchronous Edge Learning using Cloned Knowledge Distillation	Machine Learning (cs.LG)	Sang-ho Lee, Kiyoon Yoo, Nojun Kwak
2010.10442	BERT2DNN: BERT Distillation with Massive Unlabeled Data for Online E-Commerce Search	Machine Learning (cs.LG)	Yunjiang Jiang, Yue Shang, Ziyang Liu, Hongwei Shen, Yun Xiao, Wei Xiong, Sulong Xu, Weipeng Yan, Di Jin
2010.10732	SCOP: Scientific Control for Reliable Neural Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Yehui Tang, Yunhe Wang, Yixing Xu, Dacheng Tao, Chunjing Xu, Chao Xu, Chang Xu
2010.11067	Knowledge Distillation for Improved Accuracy in Spoken Question Answering	Computation and Language (cs.CL)	Chenyu You, Nuo Chen, Yuexian Zou
2010.11166	Decentralized Deep Learning using Momentum-Accelerated Consensus	Machine Learning (cs.LG)	Aditya Balu, Zhanhong Jiang, Sin Yong Tan, Chinmay Hedge, Young M Lee, Soumik Sarkar
2010.11271	Robustness-aware 2-bit quantization with real-time performance for neural network	Machine Learning (cs.LG)	Xiaobin Li, Hongxu Jiang, Shuangxi Huang, Fangzheng Tian
2010.11322	Learning to Summarize Long Texts with Memory Compression and Transfer	Computation and Language (cs.CL)	Jaehong Park, Jonathan Pilault, Christopher Pal
2010.11386	Distilling Dense Representations for Ranking using Tightly-Coupled Teachers	Information Retrieval (cs.IR)	Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin
2010.11478	Knowledge Distillation for BERT Unsupervised Domain Adaptation	Computation and Language (cs.CL)	Minho Ryu, Kichun Lee
2010.11944	Accelerating Reinforcement Learning with Learned Skill Priors	Machine Learning (cs.LG)	Karl Pertsch, Youngwoon Lee, Joseph J. Lim
2010.11980	A Joint Learning Approach based on Self-Distillation for Keyphrase Extraction from Scientific Documents	Computation and Language (cs.CL)	Tuan Manh Lai, Trung Bui, Doo Soon Kim, Quan Hung Tran
2010.12021	AutoPruning for Deep Neural Network with Dynamic Channel Masking	Computer Vision and Pattern Recognition (cs.CV)	Baopu Li, Yanwen Fan, Zhihong Pan, Gang Zhang
2010.12023	Comprehensive Attention Self-Distillation for Weakly-Supervised Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Zeyi Huang, Yang Zou, Vijayakumar Bhagavatula, Dong Huang
2010.12110	Tensor Reordering for CNN Compression	Machine Learning (cs.LG)	Matej Ulicny, Vladimir A. Krylov, Rozenn Dahyot
2010.12128	Accelerating Metropolis-Hastings with Lightweight Inference Compilation	Machine Learning (cs.LG)	Feynman Liang, Nimar Arora, Nazanin Tehrani, Yucen Li, Michael Tingley, Erik Meijer
2010.12188	Generating Long Financial Report using Conditional Variational Autoencoders with Knowledge Distillation	Machine Learning (cs.LG)	Yunpeng Ren, Ziao Wang, Yiyuan Wang, Xiaofeng Zhang
2010.12460	Adaptive Gradient Quantization for Data-Parallel SGD	Machine Learning (cs.LG)	Fartash Faghri, Iman Tabrizian, Ilia Markov, Dan Alistarh, Daniel Roy, Ali Ramezani-Kebrya
2010.12609	Iterative Graph Self-Distillation	Machine Learning (cs.LG)	Hanlin Zhang, Shuai Lin, Weiyang Liu, Pan Zhou, Jian Tang, Xiaodan Liang, Eric P. Xing
2010.12746	LCFI: A Fault Injection Tool for Studying Lossy Compression Error Propagation in HPC Programs	Distributed, Parallel, and Cluster Computing (cs.DC)	Baodi Shan, Aabid Shamji, Jiannan Tian, Guanpeng Li, Dingwen Tao
2010.13002	Pre-trained Summarization Distillation	Computation and Language (cs.CL)	Sam Shleifer, Alexander M. Rush
2010.13105	Two-stage Textual Knowledge Distillation to Speech Encoder for Spoken Language Understanding	Computation and Language (cs.CL)	Seongbin Kim, Gyuwan Kim, Seongjin Shin, Sangmin Lee
2010.13114	Empowering Knowledge Distillation via Open Set Recognition for Robust 3D Point Cloud Classification	Computer Vision and Pattern Recognition (cs.CV)	Ayush Bhardwaj, Sakshee Pimpale, Saurabh Kumar, Biplab Banerjee
2010.13160	Neuron Merging: Compensating for Pruned Neurons	Computer Vision and Pattern Recognition (cs.CV)	Woojeong Kim, Suhyun Kim, Mincheol Park, Geonseok Jeon
2010.13335	Convergence Acceleration via Chebyshev Step: Plausible Interpretation of Deep-Unfolded Gradient Descent	Machine Learning (cs.LG)	Satoshi Takabe, Tadashi Wadayama
2010.13369	Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping	Machine Learning (cs.LG)	Minjia Zhang, Yuxiong He
2010.13500	Activation Map Adaptation for Effective Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Zhiyuan Wu, Hong Qi, Yu Jiang, Minghao Zhao, Chupeng Cui, Zongmin Yang, Xinhui Xue
2010.13611	OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning	Machine Learning (cs.LG)	Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum
2010.14271	Cross-lingual Machine Reading Comprehension with Language Branch Knowledge Distillation	Computation and Language (cs.CL)	Junhao Liu, Linjun Shou, Jian Pei, Ming Gong, Min Yang, Daxin Jiang
2010.14713	CompRess: Self-Supervised Learning by Compressing Representations	Computer Vision and Pattern Recognition (cs.CV)	Soroush Abbasi Koohpayegani, Ajinkya Tejankar, Hamed Pirsiavash
2010.14714	Differentiable Channel Pruning Search	Computer Vision and Pattern Recognition (cs.CV)	Yu Zhao, Chung-Kuei Lee
2010.14803	Enhanced Blind Calibration of Uniform Linear Arrays with One-Bit Quantization by Kullback-Leibler Divergence Covariance Fitting	Signal Processing (eess.SP)	Amir Weiss, Arie Yeredor
2010.15054	Attribution Preservation in Network Compression for Reliable Network Interpretation	Machine Learning (cs.LG)	Geondo Park, June Yong Yang, Sung Ju Hwang, Eunho Yang
2010.15302	Point Cloud Attribute Compression via Successive Subspace Graph Transform	Computer Vision and Pattern Recognition (cs.CV)	Yueru Chen, Yiting Shao, Jing Wang, Ge Li, C.-C. Jay Kuo
2010.15703	Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Julieta Martinez, Jashan Shewakramani, Ting Wei Liu, Ioan Andrei Bârsan, Wenyuan Zeng, Raquel Urtasun
2010.15821	Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search	Computer Vision and Pattern Recognition (cs.CV)	Houwen Peng, Hao Du, Hongyuan Yu, Qi Li, Jing Liao, Jianlong Fu
2010.16165	Fusion-Catalyzed Pruning for Optimizing Deep Learning on Intelligent Edge Devices	Neural and Evolutionary Computing (cs.NE)	Guangli Li, Xiu Ma, Xueying Wang, Lei Liu, Jingling Xue, Xiaobing Feng
2010.16386	Audio Dequantization Using (Co)Sparse (Non)Convex Methods	Audio and Speech Processing (eess.AS)	Pavel Záviška, Pavel Rajmic, Ondřej Mokrý
2011.00215	LRA: an accelerated rough set framework based on local redundancy of attribute for feature selection	Artificial Intelligence (cs.AI)	Shuyin Xia, Wenhua Li, Guoyin Wang, Xinbo Gao, Changqing Zhang, Elisabeth Giem
2011.00241	Methods for Pruning Deep Neural Networks	Machine Learning (cs.LG)	Sunil Vadera, Salem Ameen
2011.00265	ProxylessKD: Direct Knowledge Distillation with Inherited Classifier for Face Recognition	Computer Vision and Pattern Recognition (cs.CV)	Weidong Shi, Guanghui Ren, Yunpeng Chen, Shuicheng Yan
2011.00593	MixKD: Towards Efficient Distillation of Large-scale Language Models	Computation and Language (cs.CL)	Kevin J Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin
2011.00809	Data-free Knowledge Distillation for Segmentation using Data-Enriching GAN	Computer Vision and Pattern Recognition (cs.CV)	Kaushal Bhogale
2011.01302	IOS: Inter-Operator Scheduler for CNN Acceleration	Machine Learning (cs.LG)	Yaoyao Ding, Ligeng Zhu, Zhihao Jia, Gennady Pekhimenko, Song Han
2011.01424	In Defense of Feature Mimicking for Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Guo-Hua Wang, Yifan Ge, Jianxin Wu
2011.02166	DAIS: Automatic Channel Pruning via Differentiable Annealing Indicator Search	Computer Vision and Pattern Recognition (cs.CV)	Yushuo Guan, Ning Liu, Pengyu Zhao, Zhengping Che, Kaigui Bian, Yanzhi Wang, Jian Tang
2011.02255	On Self-Distilling Graph Neural Network	Machine Learning (cs.LG)	Yuzhao Chen, Yatao Bian, Xi Xiao, Yu Rong, Tingyang Xu, Junzhou Huang
2011.02367	Federated Knowledge Distillation	Machine Learning (cs.LG)	Hyowoon Seo, Jihong Park, Seungeun Oh, Mehdi Bennis, Seong-Lyun Kim
2011.02379	Asynchrony and Acceleration in Gossip Algorithms	Distributed, Parallel, and Cluster Computing (cs.DC)	Mathieu Even, Hadrien Hendrikx, Laurent Massoulié
2011.02389	Filter Pruning using Hierarchical Group Sparse Regularization for Deep Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Kakeru Mitsuno, Takio Kurita
2011.02390	Channel Planting for Deep Neural Networks using Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Kakeru Mitsuno, Yuichiro Nomura, Takio Kurita
2011.03029	CompressAI: a PyTorch library and evaluation platform for end-to-end compression research	Computer Vision and Pattern Recognition (cs.CV)	Jean Bégaint, Fabien Racapé, Simon Feltman, Akshay Pushparaja
2011.03083	A Tunable Robust Pruning Framework Through Dynamic Network Rewiring of DNNs	Computer Vision and Pattern Recognition (cs.CV)	Souvik Kundu, Mahdi Nazemi, Peter A. Beerel, Massoud Pedram
2011.03170	GHFP: Gradually Hard Filter Pruning	Computer Vision and Pattern Recognition (cs.CV)	Linhang Cai, Zhulin An, Yongjun Xu
2011.03240	Channel Pruning via Multi-Criteria based on Weight Dependency	Computer Vision and Pattern Recognition (cs.CV)	Yangchun Yan, Chao Li, Rongzuo Guo, Kang Yang, Yongjun Xu
2011.03749	Robustness and Diversity Seeking Data-Free Knowledge Distillation	Machine Learning (cs.LG)	Pengchao Han, Jihong Park, Shiqiang Wang, Yejun Liu
2011.03770	Know What You Don't Need: Single-Shot Meta-Pruning for Attention Heads	Computation and Language (cs.CL)	Zhengyan Zhang, Fanchao Qi, Zhiyuan Liu, Qun Liu, Maosong Sun
2011.03891	Channel Pruning Guided by Spatial and Channel Attention for DNNs in Intelligent Edge Computing	Computer Vision and Pattern Recognition (cs.CV)	Mengran Liu, Weiwei Fang, Xiaodong Ma, Wenyuan Xu, Naixue Xiong, Yi Ding
2011.03970	The quantization error in a Self-Organizing Map as a contrast and colour specific indicator of single-pixel change in large random patterns	Computer Vision and Pattern Recognition (cs.CV)	John M Wandeto, Birgitta Dresp-Langley
2011.04106	Ensembled CTR Prediction via Knowledge Distillation	Machine Learning (cs.LG)	Jieming Zhu, Jinyang Liu, Weiqi Li, Jincai Lai, Xiuqiang He, Liang Chen, Zibin Zheng
2011.04586	Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound	Machine Learning (cs.LG)	Steve Hanneke, Aryeh Kontorovich
2011.04868	Neural Network Compression Via Sparse Optimization	Machine Learning (cs.LG)	Tianyi Chen, Bo Ji, Yixin Shi, Tianyu Ding, Biyi Fang, Sheng Yi, Xiao Tu
2011.04908	Stage-wise Channel Pruning for Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Mingyang Zhang, Linlin Ou
2011.04976	Conceptual Compression via Deep Structure and Texture Synthesis	Computer Vision and Pattern Recognition (cs.CV)	Jianhui Chang, Zhenghui Zhao, Chuanmin Jia, Shiqi Wang, Lingbo Yang, Jian Zhang, Siwei Ma
2011.04981	Exploring the acceleration of Nekbone on reconfigurable architectures	Distributed, Parallel, and Cluster Computing (cs.DC)	Nick Brown
2011.05390	Gaussian Compression Stream: Principle and Preliminary Results	Signal Processing (eess.SP)	Farouk Yahaya, Matthieu Puigt, Gilles Delmaire, Gilles Roussel
2011.05578	Compression Boosts Differentially Private Federated Learning	Machine Learning (cs.LG)	Raouf Kerkouche, Gergely Ács, Claude Castelluccia, Pierre Genevès
2011.05664	Distill2Vec: Dynamic Graph Representation Learning with Knowledge Distillation	Machine Learning (cs.LG)	Stefanos Antaris, Dimitrios Rafailidis
2011.05702	Invariant Deep Compressible Covariance Pooling for Aerial Scene Categorization	Computer Vision and Pattern Recognition (cs.CV)	Shidong Wang, Yi Ren, Gerard Parr, Yu Guan, Ling Shao
2011.05705	EGAD: Evolving Graph Representation Learning with Self-Attention and Knowledge Distillation for Live Video Streaming Events	Machine Learning (cs.LG)	Stefanos Antaris, Dimitrios Rafailidis, Sarunas Girdzijauskas
2011.05985	Dirichlet Pruning for Neural Network Compression	Machine Learning (cs.LG)	Kamil Adamczewski, Mijung Park
2011.06110	Efficient Knowledge Distillation for RNN-Transducer Models	Audio and Speech Processing (eess.AS)	Sankaran Panchapagesan, Daniel S. Park, Chung-Cheng Chiu, Yuan Shangguan, Qiao Liang, Alexander Gruenstein
2011.06231	Automated Model Compression by Jointly Applied Pruning and Quantization	Computer Vision and Pattern Recognition (cs.CV)	Wenting Tang, Xingxing Wei, Bo Li
2011.06295	When deep learning models on GPU can be accelerated by taking advantage of unstructured sparsity	Machine Learning (cs.LG)	Marcin Pietroń Dominik Żurek
2011.06751	Filter Pre-Pruning for Improved Fine-tuning of Quantized Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Jun Nishikawa, Ryoji Ikegaya
2011.06923	LEAN: graph-based pruning for convolutional neural networks by extracting longest chains	Machine Learning (cs.LG)	Richard Schoonhoven, Allard A. Hendriksen, Daniël M. Pelt, K. Joost Batenburg
2011.07363	RecTen: A Recursive Hierarchical Low Rank Tensor Factorization Method to Discover Hierarchical Patterns in Multi-modal Data	Information Retrieval (cs.IR)	Risul Islam, Md Omar Faruk Rokon, Evangelos E. Papalexakis, Michalis Faloutsos
2011.07449	Online Ensemble Model Compression using Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Devesh Walawalkar, Zhiqiang Shen, Marios Savvides
2011.07643	Advances in the training, pruning and enforcement of shape constraints of Morphological Neural Networks using Tropical Algebra	Machine Learning (cs.LG)	Nikolaos Dimitriadis, Petros Maragos
2011.08007	Domain Adaptive Knowledge Distillation for Driving Scene Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Divya Kothandaraman, Athira Nambiar, Anurag Mittal
2011.08009	Subtensor Quantization for Mobilenets	Computer Vision and Pattern Recognition (cs.CV)	Thu Dinh, Andrey Melnikov, Vasilios Daskalopoulos, Sek Chai
2011.08345	Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning	Machine Learning (cs.LG)	Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae, Soon-Seo Park, Han-Lim Choi
2011.08382	Learning Efficient GANs using Differentiable Masks and co-Attention Distillation	Computer Vision and Pattern Recognition (cs.CV)	Shaojie Li, Mingbao Lin, Yan Wang, Mingliang Xu, Feiyue Huang, Yongjian Wu, Ling Shao, Rongrong Ji
2011.08545	Dynamic Hard Pruning of Neural Networks at the Edge of the Internet	Machine Learning (cs.LG)	Lorenzo Valerio, Franco Maria Nardini, Andrea Passarella, Raffaele Perego
2011.08932	Analyzing and Mitigating Compression Defects in Deep Learning	Computer Vision and Pattern Recognition (cs.CV)	Max Ehrlich, Larry Davis, Ser-Nam Lim, Abhinav Shrivastava
2011.08954	Multi-agent Reinforcement Learning Accelerated MCMC on Multiscale Inversion Problem	Machine Learning (cs.LG)	Eric Chung, Yalchin Efendiev, Wing Tat Leung, Sai-Mang Pun, Zecheng Zhang
2011.09017	A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy Compression	Distributed, Parallel, and Cluster Computing (cs.DC)	Sian Jin, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao
2011.09058	Layer-Wise Data-Free CNN Compression	Computer Vision and Pattern Recognition (cs.CV)	Maxwell Horton, Yanzi Jin, Ali Farhadi, Mohammad Rastegari
2011.09113	Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation	Machine Learning (cs.LG)	Gaurav Kumar Nayak, Konda Reddy Mopuri, Anirban Chakraborty
2011.09158	Privileged Knowledge Distillation for Online Action Detection	Computer Vision and Pattern Recognition (cs.CV)	Peisen Zhao, Lingxi Xie, Ya Zhang, Yanfeng Wang, Qi Tian
2011.09361	A Knowledge Distillation Ensemble Framework for Predicting Short and Long-term Hospitalisation Outcomes from Electronic Health Records Data	Machine Learning (cs.LG)	Zina M Ibrahim, Daniel Bean, Thomas Searle, Honghan Wu, Anthony Shek, Zeljko Kraljevic, James Galloway, Sam Norton, James T Teo, Richard JB Dobson
2011.09757	KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation	Machine Learning (cs.LG)	Hao-Zhe Feng, Zhaoyang You, Minghao Chen, Tianye Zhang, Minfeng Zhu, Fei Wu, Chao Wu, Wei Chen
2011.09899	Learning in School: Multi-teacher Knowledge Inversion for Data-Free Quantization	Machine Learning (cs.LG)	Yuhang Li, Feng Zhu, Ruihao Gong, Mingzhu Shen, Fengwei Yu, Shaoqing Lu, Shi Gu
2011.09969	Neural network algorithm and its application in reactive distillation	Neural and Evolutionary Computing (cs.NE)	Huihui Wang, Ruyang Mo
2011.10015	DiffusionNet: Accelerating the solution of Time-Dependent partial differential equations using deep learning	Machine Learning (cs.LG)	Mahmoud Asem
2011.10065	Anderson acceleration of coordinate descent	Machine Learning (stat.ML)	Quentin Bertrand, Mathurin Massias
2011.10170	An Efficient End-to-End Deep Learning Training Framework via Fine-Grained Pattern-Based Pruning	Computer Vision and Pattern Recognition (cs.CV)	Chengming Zhang, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Yanzhi Wang, Bin Ren, Shuaiwen Leon Song, Dingwen Tao
2011.10290	Image Denoising by Gaussian Patch Mixture Model and Low Rank Patches	Computer Vision and Pattern Recognition (cs.CV)	Jing Guo (1), Shuping Wang (1), Chen Luo (1), Qiyu Jin (1), Michael Kwok-Po Ng (2) ((1) School of Mathematical Science, Inner Mongolia University, Hohhot, China, (2) Department of Mathematics, University of Hong Kong, Pokfulam, Hong Kong, China)
2011.10469	Empirical Evaluation of Deep Learning Model Compression Techniques on the WaveNet Vocoder	Machine Learning (cs.LG)	Sam Davis, Giuseppe Coccia, Sam Gooch, Julian Mack
2011.10520	Continuous Pruning of Deep Convolutional Networks Using Selective Weight Decay	Neural and Evolutionary Computing (cs.NE)	Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, Thomas Hannagan, David Bertrand
2011.10680	HAWQV3: Dyadic Neural Network Quantization	Computer Vision and Pattern Recognition (cs.CV)	Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael W. Mahoney, Kurt Keutzer
2011.10704	Neural Group Testing to Accelerate Deep Learning	Machine Learning (cs.LG)	Weixin Liang, James Zou
2011.11108	Multiresolution Knowledge Distillation for Anomaly Detection	Computer Vision and Pattern Recognition (cs.CV)	Mohammadreza Salehi, Niousha Sadjadi, Soroosh Baselizadeh, Mohammad Hossein Rohban, Hamid R. Rabiee
2011.11358	Synthesis and Pruning as a Dynamic Compression Strategy for Efficient Deep Neural Networks	Artificial Intelligence (cs.AI)	Alastair Finlinson, Sotiris Moschoyiannis
2011.11846	AutoWeka4MCPS-AVATAR: Accelerating Automated Machine Learning Pipeline Composition and Optimisation	Machine Learning (cs.LG)	Tien-Dung Nguyen, Bogdan Gabrys, Katarzyna Musial
2011.12641	Auto Graph Encoder-Decoder for Model Compression and Network Acceleration	Computer Vision and Pattern Recognition (cs.CV)	Sixing Yu, Arya Mazaheri, Ali Jannesari
2011.12913	torchdistill: A Modular, Configuration-Driven Framework for Knowledge Distillation	Machine Learning (cs.LG)	Yoshitomo Matsubara
2011.12984	Enabling GPU Accelerated Computing in the SUNDIALS Time Integration Library	Distributed, Parallel, and Cluster Computing (cs.DC)	Cody J. Balos, David J. Gardner, Carol S. Woodward, Daniel R. Reynolds
2011.13000	Ax-BxP: Approximate Blocked Computation for Precision-Reconfigurable Deep Neural Network Acceleration	Machine Learning (cs.LG)	Reena Elangovan, Shubham Jain, Anand Raghunathan
2011.13256	Channel-wise Distillation for Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Changyong Shu, Yifan Liu, Jianfei Gao, Lin Xu, Chunhua Shen
2011.13772	Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias towards Low Rank	Machine Learning (cs.LG)	Hung-Hsu Chou, Carsten Gieshoff, Johannes Maly, Holger Rauhut
2011.13894	Efficient Scene Compression for Visual-based Localization	Computer Vision and Pattern Recognition (cs.CV)	Marcela Mera-Trujillo, Benjamin Smith, Victor Fragoso
2011.14058	Efficient Attention Network: Accelerate Attention by Searching Where to Plug	Computer Vision and Pattern Recognition (cs.CV)	Zhongzhan Huang, Senwei Liang, Mingfu Liang, Wei He, Haizhao Yang
2011.14266	Distilled Thompson Sampling: Practical and Efficient Thompson Sampling via Imitation Learning	Machine Learning (cs.LG)	Hongseok Namkoong, Samuel Daulton, Eytan Bakshy
2011.14356	Layer Pruning via Fusible Residual Convolutional Block for Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Pengtao Xu, Jian Cao, Fanhua Shang, Wenyu Sun, Pu Li
2011.14554	A Selective Survey on Versatile Knowledge Distillation Paradigm for Neural Network Models	Machine Learning (cs.LG)	Jeong-Hoe Ku, JiHun Oh, YoungYoon Lee, Gaurav Pooniwala, SangJeong Lee
2011.14563	Learnable Motion Coherence for Correspondence Pruning	Computer Vision and Pattern Recognition (cs.CV)	Yuan Liu, Lingjie Liu, Cheng Lin, Zhen Dong, Wenping Wang
2011.14586	FactorizeNet: Progressive Depth Factorization for Efficient Network Architecture Exploration Under Quantization Constraints	Computer Vision and Pattern Recognition (cs.CV)	Stone Yun, Alexander Wong
2011.14691	KD-Lib: A PyTorch library for Knowledge Distillation, Pruning and Quantization	Machine Learning (cs.LG)	Het Shah, Avishree Khare, Neelay Shah, Khizir Siddiqui
2012.00083	Using dynamical quantization to perform split attempts in online tree regressors	Machine Learning (cs.LG)	Saulo Martiello Mastelini, Andre Carlos Ponce de Leon Ferreira de Carvalho
2012.00124	Extreme Model Compression for On-device Natural Language Understanding	Computation and Language (cs.CL)	Kanthashree Mysore Sathyendra, Samridhi Choudhary, Leah Nicolich-Henkin
2012.00138	Robust error bounds for quantised and pruned neural networks	Machine Learning (cs.LG)	Jiaqi Li, Ross Drummond, Stephen R. Duncan
2012.00165	An accelerated hybrid data-driven/model-based approach for poroelasticity problems with multi-fidelity multi-physics data	Machine Learning (cs.LG)	Bahador Bahmani, WaiChing Sun
2012.00194	Solvable Model for Inheriting the Regularization through Knowledge Distillation	Machine Learning (cs.LG)	Luca Saglietti, Lenka Zdeborová
2012.00328	Low Bandwidth Video-Chat Compression using Deep Generative Models	Computer Vision and Pattern Recognition (cs.CV)	Maxime Oquab, Pierre Stock, Oran Gafni, Daniel Haziza, Tao Xu, Peizhao Zhang, Onur Celebi, Yana Hasson, Patrick Labatut, Bobo Bose-Kolanu, Thibault Peyronel, Camille Couprie
2012.00468	Boosting CNN-based primary quantization matrix estimation of double JPEG images via a classification-like architecture	Computer Vision and Pattern Recognition (cs.CV)	Benedetta Tondi, Andrea Costranzo, Dequ Huang, Bin Li
2012.00573	Multi-level Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Fei Ding, Feng Luo, Hongxin Hu, Yin Yang
2012.00596	6.7ms on Mobile with over 78% ImageNet Accuracy: Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration	Machine Learning (cs.LG)	Zhengang Li, Geng Yuan, Wei Niu, Yanyu Li, Pu Zhao, Yuxuan Cai, Xuan Shen, Zheng Zhan, Zhenglun Kong, Qing Jin, Zhiyu Chen, Sijia Liu, Kaiyuan Yang, Bin Ren, Yanzhi Wang, Xue Lin
2012.00632	Communication-Efficient Federated Distillation	Machine Learning (cs.LG)	Felix Sattler, Arturo Marban, Roman Rischke, Wojciech Samek
2012.00650	Decomposition, Compression, and Synthesis (DCS)-based Video Coding: A Neural Exploration via Resolution-Adaptive Learning	Computer Vision and Pattern Recognition (cs.CV)	Ming Lu, Tong Chen, Dandan Ding, Fengqing Zhu, Zhan Ma
2012.00724	Assessing and Accelerating Coverage in Deep Reinforcement Learning	Machine Learning (cs.LG)	Arpan Kusari
2012.00996	An Once-for-All Budgeted Pruning Framework for ConvNets Considering Input Resolution	Computer Vision and Pattern Recognition (cs.CV)	Wenyu Sun, Jian Cao, Pengtao Xu, Xiangcheng Liu, Pu Li
2012.01204	Unsupervised Neural Domain Adaptation for Document Image Binarization	Computer Vision and Pattern Recognition (cs.CV)	Francisco J. Castellanos, Antonio-Javier Gallego, Jorge Calvo-Zaragoza
2012.01266	Meta-KD: A Meta Knowledge Distillation Framework for Language Model Compression across Domains	Computation and Language (cs.CL)	Haojie Pan, Chengyu Wang, Minghui Qiu, Yichang Zhang, Yaliang Li, Jun Huang
2012.01604	Reliable Model Compression via Label-Preservation-Aware Loss Functions	Computer Vision and Pattern Recognition (cs.CV)	Vinu Joseph, Shoaib Ahmed Siddiqui, Aditya Bhaskara, Ganesh Gopalakrishnan, Saurav Muralidharan, Michael Garland, Sheraz Ahmed, Andreas Dengel
2012.02294	Accelerating Text Mining Using Domain-Specific Stop Word Lists	Information Retrieval (cs.IR)	Farah Alshanik, Amy Apon, Alexander Herzog, Ilya Safro, Justin Sybrandt
2012.02672	Accelerating Road Sign Ground Truth Construction with Knowledge Graph and Machine Learning	Artificial Intelligence (cs.AI)	Ji Eun Kim, Cory Henson, Kevin Huang, Tuan A. Tran, Wan-Yi Lin
2012.02909	Knowledge Distillation Thrives on Data Augmentation	Computer Vision and Pattern Recognition (cs.CV)	Huan Wang, Suhas Lohit, Michael Jones, Yun Fu
2012.02910	Cosine-Pruned Medial Axis: A new method for isometric equivariant and noise-free medial axis extraction	Computer Vision and Pattern Recognition (cs.CV)	Diego Patiño, John Branch
2012.02911	Multi-head Knowledge Distillation for Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Huan Wang, Suhas Lohit, Michael Jones, Yun Fu
2012.03089	Understanding Interpretability by generalized distillation in Supervised Classification	Machine Learning (cs.LG)	Adit Agarwal, Dr. K.K. Shukla, Arjan Kuijper, Anirban Mukhopadhyay
2012.03096	Parallel Blockwise Knowledge Distillation for Deep Neural Network Compression	Machine Learning (cs.LG)	Cody Blakeney, Xiaomin Li, Yan Yan, Ziliang Zong
2012.03236	Cross-Layer Distillation with Semantic Calibration	Computer Vision and Pattern Recognition (cs.CV)	Defang Chen, Jian-Ping Mei, Yuan Zhang, Can Wang, Zhe Wang, Yan Feng, Chun Chen
2012.03653	DiffPrune: Neural Network Pruning with Deterministic Approximate Binary Gates and $L_0$ Regularization	Machine Learning (stat.ML)	Yaniv Shulman
2012.03860	Modeling the effects of dynamic range compression on signals in noise	Audio and Speech Processing (eess.AS)	Ryan M. Corey, Andrew C. Singer
2012.03907	Model Compression Using Optimal Transport	Computer Vision and Pattern Recognition (cs.CV)	Suhas Lohit, Michael Jones
2012.04061	Improved Convergence Rates for Non-Convex Federated Learning with Compression	Machine Learning (stat.ML)	Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon
2012.04201	GPU Accelerated Exhaustive Search for Optimal Ensemble of Black-Box Optimization Algorithms	Machine Learning (cs.LG)	Jiwei Liu, Bojan Tunguz, Gilberto Titericz
2012.04228	Accelerating Continuous Normalizing Flow with Trajectory Polynomial Regularization	Machine Learning (cs.LG)	Han-Hsien Huang, Mi-Yen Yeh
2012.04357	DE-RRD: A Knowledge Distillation Framework for Recommender System	Machine Learning (cs.LG)	SeongKu Kang, Junyoung Hwang, Wonbin Kweon, Hwanjo Yu
2012.04584	Distilling Knowledge from Reader to Retriever for Question Answering	Computation and Language (cs.CL)	Gautier Izacard, Edouard Grave
2012.04649	A novel machine learning-based optimization algorithm (ActivO) for accelerating simulation-driven engine design	Machine Learning (cs.LG)	Opeoluwa Owoyele, Pinaki Pal
2012.04839	Robust Domain Randomised Reinforcement Learning through Peer-to-Peer Distillation	Machine Learning (cs.LG)	Chenyang Zhao, Timothy Hospedales
2012.04915	Progressive Network Grafting for Few-Shot Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Chengchao Shen, Xinchao Wang, Youtan Yin, Jie Song, Sihui Luo, Mingli Song
2012.04964	On Knowledge Distillation for Direct Speech Translation	Computation and Language (cs.CL)	Marco Gaido, Mattia A. Di Gangi, Matteo Negri, Marco Turchi
2012.05578	Large-Scale Generative Data-Free Distillation	Machine Learning (cs.LG)	Liangchen Luo, Mark Sandler, Zi Lin, Andrey Zhmoginov, Andrew Howard
2012.06048	Reinforced Multi-Teacher Selection for Knowledge Distillation	Computation and Language (cs.CL)	Fei Yuan, Linjun Shou, Jian Pei, Wutao Lin, Ming Gong, Yan Fu, Daxin Jiang
2012.06153	Improving Task-Agnostic BERT Distillation with Layer Mapping Search	Computation and Language (cs.CL)	Xiaoqi Jiao, Huating Chang, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, Qun Liu
2012.06281	Trash Talk: Accelerating Garbage Collection on Integrated GPUs is Worthless	Distributed, Parallel, and Cluster Computing (cs.DC)	Mohammad Dashti, Alexandra Fedorova
2012.06289	ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting	Machine Learning (cs.LG)	Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
2012.06380	Parallelized Rate-Distortion Optimized Quantization Using Deep Learning	Machine Learning (cs.LG)	Dana Kianfar, Auke Wiggers, Amir Said, Reza Pourreza, Taco Cohen
2012.06659	DeCoAR 2.0: Deep Contextualized Acoustic Representations with Vector Quantization	Audio and Speech Processing (eess.AS)	Shaoshi Ling, Yuzong Liu
2012.06746	Periocular in the Wild Embedding Learning with Cross-Modal Consistent Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yoon Gyo Jung, Jaewoo Park, Cheng Yaw Low, Leslie Ching Ow Tiong, Andrew Beng Jin Teoh
2012.06943	Discriminative Pre-training for Low Resource Title Compression in Conversational Grocery	Computation and Language (cs.CL)	Snehasish Mukherjee, Phaniram Sayapaneni, Shankar Subramanya
2012.06956	Learn-Prune-Share for Lifelong Learning	Machine Learning (cs.LG)	Zifeng Wang, Tong Jian, Kaushik Chowdhury, Yanzhi Wang, Jennifer Dy, Stratis Ioannidis
2012.07335	LRC-BERT: Latent-representation Contrastive Knowledge Distillation for Natural Language Understanding	Computation and Language (cs.CL)	Hao Fu, Shaojun Zhou, Qihong Yang, Junjie Tang, Guiquan Liu, Kaikui Liu, Xiaolong Li
2012.07463	Parameter-Efficient Transfer Learning with Diff Pruning	Computation and Language (cs.CL)	Demi Guo, Alexander M. Rush, Yoon Kim
2012.07535	Ensemble Distillation Approaches for Grammatical Error Correction	Computation and Language (cs.CL)	Yassir Fathullah, Mark Gales, Andrey Malinin
2012.08112	Amata: An Annealing Mechanism for Adversarial Training Acceleration	Machine Learning (cs.LG)	Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu
2012.08241	CosSGD: Nonlinear Quantization for Communication-efficient Federated Learning	Machine Learning (cs.LG)	Yang He, Maximilian Zenk, Mario Fritz
2012.08282	Robots Understanding Contextual Information in Human-Centered Environments using Weakly Supervised Mask Data Distillation	Computer Vision and Pattern Recognition (cs.CV)	Daniel Dworakowski, Goldie Nejat
2012.08420	Exploring Neural Networks Quantization via Layer-Wise Quantization Analysis	Machine Learning (cs.LG)	Shachar Gluska, Mark Grobman
2012.08660	Accelerating Distributed Online Meta-Learning via Multi-Agent Collaboration under Limited Communication	Machine Learning (cs.LG)	Sen Lin, Mehmet Dedeoglu, Junshan Zhang
2012.08674	Wasserstein Contrastive Representation Distillation	Machine Learning (cs.LG)	Liqun Chen, Zhe Gan, Dong Wang, Jingjing Liu, Ricardo Henao, Lawrence Carin
2012.08749	Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks	Machine Learning (cs.LG)	Xiangyu Chang, Yingcong Li, Samet Oymak, Christos Thrampoulidis
2012.08859	Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces	Machine Learning (cs.LG)	Bert Moons, Parham Noorzad, Andrii Skliar, Giovanni Mariani, Dushyant Mehta, Chris Lott, Tijmen Blankevoort
2012.09102	FedADC: Accelerated Federated Learning with Drift Control	Machine Learning (cs.LG)	Emre Ozfatura, Kerem Ozfatura, Deniz Gunduz
2012.09243	Neural Pruning via Growing Regularization	Computer Vision and Pattern Recognition (cs.CV)	Huan Wang, Can Qin, Yulun Zhang, Yun Fu
2012.09259	ISD: Self-Supervised Learning by Iterative Similarity Distillation	Computer Vision and Pattern Recognition (cs.CV)	Ajinkya Tejankar, Soroush Abbasi Koohpayegani, Vipin Pillai, Paolo Favaro, Hamed Pirsiavash
2012.09413	Computation-Efficient Knowledge Distillation via Uncertainty-Aware Mixup	Computer Vision and Pattern Recognition (cs.CV)	Guodong Xu, Ziwei Liu, Chen Change Loy
2012.09511	Solving large permutation flow-shop scheduling problems on GPU-accelerated supercomputers	Distributed, Parallel, and Cluster Computing (cs.DC)	Jan Gmys
2012.09708	Efficient CNN-LSTM based Image Captioning using Neural Network Compression	Computer Vision and Pattern Recognition (cs.CV)	Harshit Rampal, Aman Mohanty
2012.09816	Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning	Machine Learning (cs.LG)	Zeyuan Allen-Zhu, Yuanzhi Li
2012.10079	A Surrogate Lagrangian Relaxation-based Model Compression for Deep Neural Networks	Machine Learning (cs.LG)	Deniz Gurevin, Shanglin Zhou, Lynn Pepin, Bingbing Li, Mikhail Bragin, Caiwen Ding, Fei Miao
2012.10138	Resource-efficient DNNs for Keyword Spotting using Neural Architecture Search and Quantization	Audio and Speech Processing (eess.AS)	David Peter, Wolfgang Roth, Franz Pernkopf
2012.11187	Diverse Knowledge Distillation for End-to-End Person Search	Computer Vision and Pattern Recognition (cs.CV)	Xinyu Zhang, Xinlong Wang, Jia-Wang Bian, Chunhua Shen, Mingyu You
2012.11230	DAQ: Distribution-Aware Quantization for Deep Image Super-Resolution Networks	Computer Vision and Pattern Recognition (cs.CV)	Cheeun Hong, Heewon Kim, Junghun Oh, Kyoung Mu Lee
2012.11691	Alleviating Noisy Data in Image Captioning with Cooperative Distillation	Computer Vision and Pattern Recognition (cs.CV)	Pierre Dognin, Igor Melnyk, Youssef Mroueh, Inkit Padhi, Mattia Rigotti, Jarret Ross, Yair Schiff
2012.11804	To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices	Machine Learning (cs.LG)	Liang Li, Dian Shi, Ronghui Hou, Hui Li, Miao Pan, Zhu Han
2012.12496	Active Sampling for Accelerated MRI with Low-Rank Tensors	Computer Vision and Pattern Recognition (cs.CV)	Zichang He, Bo Zhao, Zheng Zhang
2012.12843	EQ-Net: A Unified Deep Learning Framework for Log-Likelihood Ratio Estimation and Quantization	Machine Learning (cs.LG)	Marius Arvinte, Ahmed H. Tewfik, Sriram Vishwanath
2012.12877	Training data-efficient image transformers & distillation through attention	Computer Vision and Pattern Recognition (cs.CV)	Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, Hervé Jégou
2012.13091	Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search	Machine Learning (cs.LG)	Yonggan Fu, Zhongzhi Yu, Yongan Zhang, Yingyan Lin
2012.13716	Hybrid and Non-Uniform quantization methods using retro synthesis data for efficient inference	Computer Vision and Pattern Recognition (cs.CV)	Tej pratap GVSL, Raja Kumar
2012.13762	Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Tuan Hoang, Thanh-Toan Do, Tam V. Nguyen, Ngai-Man Cheung
2012.14022	ALP-KD: Attention-Based Layer Projection for Knowledge Distillation	Computation and Language (cs.CL)	Peyman Passban, Yimeng Wu, Mehdi Rezagholizadeh, Qun Liu
2012.14682	Accelerating Pre-trained Language Models via Calibrated Cascade	Computation and Language (cs.CL)	Lei Li, Yankai Lin, Shuhuai Ren, Deli Chen, Xuancheng Ren, Peng Li, Jie Zhou, Xu Sun
2012.14830	Accelerated NMR Spectroscopy: Merge Optimization with Deep Learning	Machine Learning (cs.LG)	Zi Wang, Di Guo, Yihui Huang, Zhangren Tu, Vladislav Orekhov, Xiaobo Qu
2012.15321	Leveraging User Access Patterns and Advanced Cyberinfrastructure to Accelerate Data Delivery from Shared-use Scientific Observatories	Distributed, Parallel, and Cluster Computing (cs.DC)	Yubo Qin, Ivan Rodero, Anthony Simonet, Charles Meertens, Daniel Reiner, James Riley, Manish Parashar
2012.15359	Knowledge Distillation with Adaptive Asymmetric Label Sharpening for Semi-supervised Fracture Detection in Chest X-rays	Computer Vision and Pattern Recognition (cs.CV)	Yirui Wang, Kang Zheng, Chi-Tung Chang, Xiao-Yun Zhou, Zhilin Zheng, Lingyun Huang, Jing Xiao, Le Lu, Chien-Hung Liao, Shun Miao
2012.15439	SID: Incremental Learning for Anchor-Free Object Detection via Selective and Inter-Related Distillation	Computer Vision and Pattern Recognition (cs.CV)	Can Peng, Kun Zhao, Sam Maksoud, Meng Li, Brian C. Lovell
2012.15455	Exploring Monolingual Data for Neural Machine Translation with Knowledge Distillation	Computation and Language (cs.CL)	Alham Fikri Aji, Kenneth Heafield
2012.15495	Towards Zero-Shot Knowledge Distillation for Natural Language Processing	Computation and Language (cs.CL)	Ahmad Rashid, Vasileios Lioutas, Abbas Ghaddar, Mehdi Rezagholizadeh
2012.15701	BinaryBERT: Pushing the Limit of BERT Quantization	Computation and Language (cs.CL)	Haoli Bai, Wei Zhang, Lu Hou, Lifeng Shang, Jing Jin, Xin Jiang, Qun Liu, Michael Lyu, Irwin King
2012.15828	MiniLMv2: Multi-Head Self-Attention Relation Distillation for Compressing Pretrained Transformers	Computation and Language (cs.CL)	Wenhui Wang, Hangbo Bao, Shaohan Huang, Li Dong, Furu Wei
2101.01321	I-BERT: Integer-only BERT Quantization	Computation and Language (cs.CL)	Sehoon Kim, Amir Gholami, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer
2101.01689	Label Augmentation via Time-based Knowledge Distillation for Financial Anomaly Detection	Machine Learning (cs.LG)	Hongda Shen, Eren Kursun
2101.01710	Learning Accurate Dense Correspondences and When to Trust Them	Computer Vision and Pattern Recognition (cs.CV)	Prune Truong, Martin Danelljan, Luc Van Gool, Radu Timofte
2101.01881	Modality-specific Distillation	Computer Vision and Pattern Recognition (cs.CV)	Woojeong Jin, Maziar Sanjabi, Shaoliang Nie, Liang Tan, Xiang Ren, Hamed Firooz
2101.02338	Max-Affine Spline Insights Into Deep Network Pruning	Machine Learning (cs.LG)	Randall Balestriero, Haoran You, Zhihan Lu, Yutong Kou, Yingyan Lin, Richard Baraniuk
2101.02388	Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed	Machine Learning (cs.LG)	Eric Luhman, Troy Luhman
2101.02663	L2PF -- Learning to Prune Faster	Computer Vision and Pattern Recognition (cs.CV)	Manoj-Rohit Vemparala, Nael Fasfous, Alexander Frickenstein, Mhd Ali Moraly, Aquib Jamal, Lukas Frickenstein, Christian Unger, Naveen-Shankar Nagaraja, Walter Stechele
2101.02916	Towards Accelerating Training of Batch Normalization: A Manifold Perspective	Machine Learning (cs.LG)	Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma
2101.03304	Quantization optimized with respect to the Haar basis	Signal Processing (eess.SP)	Shu Nakamura
2101.04354	Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks	Machine Learning (cs.LG)	Karina Vasquez, Yeshwanth Venkatesha, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
2101.04731	SEED: Self-supervised Distillation For Visual Representation	Computer Vision and Pattern Recognition (cs.CV)	Zhiyuan Fang, Jianfeng Wang, Lijuan Wang, Lei Zhang, Yezhou Yang, Zicheng Liu
2101.04935	ABS: Automatic Bit Sharing for Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Jing Liu, Bohan Zhuang, Peng Chen, Yong Guo, Chunhua Shen, Jianfei Cai, Mingkui Tan
2101.05453	On the quantization of recurrent neural networks	Machine Learning (cs.LG)	Jian Li, Raziel Alvarez
2101.05471	Towards Practical Adam: Non-Convexity, Convergence Theory, and Mini-Batch Acceleration	Machine Learning (cs.LG)	Congliang Chen, Li Shen, Fangyu Zou, Wei Liu
2101.05624	Adversarially Robust and Explainable Model Compression with On-Device Personalization for Text Classification	Machine Learning (cs.LG)	Yao Qiang, Supriya Tumkur Suresh Kumar, Marco Brocanelli, Dongxiao Zhu
2101.05888	GPU Acceleration for Synthetic Aperture Sonar Image Reconstruction	Signal Processing (eess.SP)	Isaac D. Gerg, Daniel C. Brown, Stephen G. Wagner, Daniel Cook, Brian N. O'Donnell, Thomas Benson, Thomas C. Montgomery
2101.05930	Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks	Machine Learning (cs.LG)	Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma
2101.05938	KDLSQ-BERT: A Quantized Bert Combining Knowledge Distillation with Learned Step Size Quantization	Computation and Language (cs.CL)	Jing Jin, Cai Liang, Tiancheng Wu, Liqin Zou, Zhiliang Gan
2101.05996	Convolutional Neural Network with Pruning Method for Handwritten Digit Recognition	Computer Vision and Pattern Recognition (cs.CV)	Mengyu Chen
2101.06407	ACP: Automatic Channel Pruning via Clustering and Swarm Intelligence Optimization for CNN	Computer Vision and Pattern Recognition (cs.CV)	Jingfei Chang, Yang Lu, Ping Xue, Yiqun Xu, Zhen Wei
2101.06608	Network Automatic Pruning: Start NAP and Take a Nap	Computer Vision and Pattern Recognition (cs.CV)	Wenyuan Zeng, Yuwen Xiong, Raquel Urtasun
2101.06686	KCP: Kernel Cluster Pruning for Dense Labeling Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Po-Hsiang Yu, Sih-Sian Wu, Liang-Gee Chen
2101.06993	Deep Compression of Neural Networks for Fault Detection on Tennessee Eastman Chemical Processes	Machine Learning (cs.LG)	Mingxuan Li, Yuanxun Shao
2101.07086	Model Compression for Domain Adaptation through Causal Effect Estimation	Computation and Language (cs.CL)	Guy Rotman, Amir Feder, Roi Reichart
2101.07308	Knowledge Distillation Methods for Efficient Unsupervised Adaptation Across Multiple Domains	Computer Vision and Pattern Recognition (cs.CV)	Le Thanh Nguyen-Meidine, Atif Belal, Madhu Kiran, Jose Dolz, Louis-Antoine Blais-Morin, Eric Granger
2101.07344	Accelerating Deep Learning Inference via Learned Caches	Machine Learning (cs.LG)	Arjun Balasubramanian, Adarsh Kumar, Yuhan Liu, Han Cao, Shivaram Venkataraman, Aditya Akella
2101.07731	TC-DTW: Accelerating Multivariate Dynamic Time Warping Through Triangle Inequality and Point Clustering	Machine Learning (cs.LG)	Daniel Shen, Min Chi
2101.07831	Multi-Task Network Pruning and Embedded Optimization for Real-time Deployment in ADAS	Computer Vision and Pattern Recognition (cs.CV)	Flora Dellinger, Thomas Boulay, Diego Mendoza Barrenechea, Said El-Hachimi, Isabelle Leang, Fabian Bürger
2101.07968	DynaComm: Accelerating Distributed CNN Training between Edges and Clouds through Dynamic Communication Scheduling	Distributed, Parallel, and Cluster Computing (cs.DC)	Shangming Cai, Dongsheng Wang, Haixia Wang, Yongqiang Lyu, Guangquan Xu, Xi Zheng, Athanasios V. Vasilakos
2101.07985	Non-Parametric Adaptive Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Mingbao Lin, Rongrong Ji, Shaojie Li, Yan Wang, Yongjian Wu, Feiyue Huang, Qixiang Ye
2101.08106	Learning to Augment for Data-Scarce Domain BERT Knowledge Distillation	Computation and Language (cs.CL)	Lingyun Feng, Minghui Qiu, Yaliang Li, Hai-Tao Zheng, Ying Shen
2101.08212	PiChu: Accelerating Block Broadcasting in Blockchain Networks with Pipelining and Chunking	Distributed, Parallel, and Cluster Computing (cs.DC)	Kaushik Ayinala, Baek-Young Choi, Sejun Song
2101.08393	Distilling Interpretable Models into Human-Readable Code	Machine Learning (cs.LG)	Walker Ravina, Ethan Sterling, Olexiy Oryeshko, Nathan Bell, Honglei Zhuang, Xuanhui Wang, Yonghui Wu, Alexander Grushetsky
2101.08430	Generative Zero-shot Network Quantization	Computer Vision and Pattern Recognition (cs.CV)	Xiangyu He, Qinghao Hu, Peisong Wang, Jian Cheng
2101.08763	GPU-Accelerated Optimizer-Aware Evaluation of Submodular Exemplar Clustering	Distributed, Parallel, and Cluster Computing (cs.DC)	Philipp-Jan Honysz, Sebastian Buschjäger, Katharina Morik
2101.08878	Efficient MPI-based Communication for GPU-Accelerated Dask Applications	Distributed, Parallel, and Cluster Computing (cs.DC)	Aamir Shafi, Jahanzeb Maqbool Hashmi, Hari Subramoni, Dhabaleswar K. Panda
2101.08890	Distilling Large Language Models into Tiny and Effective Students using pQRNN	Computation and Language (cs.CL)	Prabhu Kaliamoorthi, Aditya Siddhant, Edward Li, Melvin Johnson
2101.08940	Hessian-Aware Pruning and Optimal Neural Implant	Computer Vision and Pattern Recognition (cs.CV)	Shixing Yu, Zhewei Yao, Amir Gholami, Zhen Dong, Michael W Mahoney, Kurt Keutzer
2101.09650	GST: Group-Sparse Training for Accelerating Deep Reinforcement Learning	Machine Learning (cs.LG)	Juhyoung Lee, Sangyeob Kim, Sangjin Kim, Wooyoung Jo, Hoi-Jun Yoo
2101.09671	Pruning and Quantization for Deep Neural Network Acceleration: A Survey	Computer Vision and Pattern Recognition (cs.CV)	Tailin Liang, John Glossner, Lei Wang, Shaobo Shi
2101.09693	A2P-MANN: Adaptive Attention Inference Hops Pruned Memory-Augmented Neural Networks	Computation and Language (cs.CL)	Mohsen Ahmadzadeh, Mehdi Kamal, Ali Afzali-Kusha, Massoud Pedram
2101.10157	Performance of Cell-Free MmWave Massive MIMO Systems with Fronthaul Compression and DAC Quantization	Signal Processing (eess.SP)	In-soo Kim, Junil Choi
2101.10203	ISP Distillation	Computer Vision and Pattern Recognition (cs.CV)	Eli Schwartz, Alex Bronstein, Raja Giryes
2101.10280	Deep Epidemiological Modeling by Black-box Knowledge Distillation: An Accurate Deep Learning Model for COVID-19	Machine Learning (cs.LG)	Dongdong Wang, Shunpu Zhang, Liqiang Wang
2101.10552	A Unified Paths Perspective for Pruning at Initialization	Machine Learning (cs.LG)	Thomas Gebhart, Udit Saxena, Paul Schrater
2101.10761	An Efficient Statistical-based Gradient Compression Technique for Distributed Training Systems	Machine Learning (cs.LG)	Ahmed M. Abdelmoniem, Ahmed Elzanaty, Mohamed-Slim Alouini, Marco Canini
2101.11186	Evolutionary Generative Adversarial Networks with Crossover Based Knowledge Distillation	Machine Learning (cs.LG)	Junjie Li, Junwei Zhang, Xiaoyu Gong, Shuai Lü
2101.11353	Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression	Machine Learning (cs.LG)	Yufei Cui, Ziquan Liu, Qiao Li, Yu Mao, Antoni B. Chan, Chun Jason Xue
2101.11369	B-spline Parameterized Joint Optimization of Reconstruction and K-space Trajectories (BJORK) for Accelerated 2D MRI	Signal Processing (eess.SP)	Guanhua Wang, Tianrui Luo, Jon-Fredrik Nielsen, Douglas C. Noll, Jeffrey A. Fessler
2101.11376	Learning Abstract Representations through Lossy Compression of Multi-Modal Signals	Machine Learning (cs.LG)	Charles Wilmot, Jochen Triesch
2101.11674	HDIB1M -- Handwritten Document Image Binarization 1 Million Dataset	Computer Vision and Pattern Recognition (cs.CV)	Kaustubh Sadekar, Prajwal Singh, Shanmuganathan Raman
2101.11714	TT-Rec: Tensor Train Compression for Deep Learning Recommendation Models	Machine Learning (cs.LG)	Chunxing Yin, Bilge Acun, Xing Liu, Carole-Jean Wu
2101.11800	AdaSpring: Context-adaptive and Runtime-evolutionary Deep Model Compression for Mobile Applications	Machine Learning (cs.LG)	Sicong Liu, Bin Guo, Ke Ma, Zhiwen Yu, Junzhao Du
2101.12414	Low Rank Forecasting	Machine Learning (stat.ML)	Shane Barratt, Yining Dong, Stephen Boyd
2102.00160	Deep Model Compression based on the Training History	Computer Vision and Pattern Recognition (cs.CV)	S.H.Shabbeer Basha, Mohammad Farazuddin, Viswanath Pulabaigari, Shiv Ram Dubey, Snehasis Mukherjee
2102.00390	AACP: Model Compression by Accurate and Automatic Channel Pruning	Computer Vision and Pattern Recognition (cs.CV)	Lanbo Lin, Yujiu Yang, Zhenhua Guo
2102.00554	Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks	Machine Learning (cs.LG)	Torsten Hoefler, Dan Alistarh, Tal Ben-Nun, Nikoli Dryden, Alexandra Peste
2102.00650	Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective	Machine Learning (cs.LG)	Helong Zhou, Liangchen Song, Jiajie Chen, Ye Zhou, Guoli Wang, Junsong Yuan, Qian Zhang
2102.00667	Probabilistic Learning Vector Quantization on Manifold of Symmetric Positive Definite Matrices	Machine Learning (cs.LG)	Fengzhen Tang, Haifeng Feng, Peter Tino, Bailu Si, Daxiong Ji
2102.00783	An End-To-End-Trainable Iterative Network Architecture for Accelerated Radial Multi-Coil 2D Cine MR Image Reconstruction	Machine Learning (cs.LG)	Andreas Kofler, Markus Haltmeier, Tobias Schaeffter, Christoph Kolbitsch
2102.01345	Fast Exploration of Weight Sharing Opportunities for CNN Compression	Machine Learning (cs.LG)	Etienne Dupuis, David Novo, Ian O'Connor, Alberto Bosio
2102.01386	AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning	Machine Learning (cs.LG)	Yuhan Liu, Saurabh Agarwal, Shivaram Venkataraman
2102.01578	CTC-based Compression for Direct Speech Translation	Computation and Language (cs.CL)	Marco Gaido, Mauro Cettolo, Matteo Negri, Marco Turchi
2102.01593	FEDZIP: A Compression Framework for Communication-Efficient Federated Learning	Machine Learning (cs.LG)	Amirhossein Malekijoo, Mohammad Javad Fadaeieslam, Hanieh Malekijou, Morteza Homayounfar, Farshid Alizadeh-Shabdiz, Reza Rawassizadeh
2102.02147	Fixed-point Quantization of Convolutional Neural Networks for Quantized Inference on Embedded Platforms	Computer Vision and Pattern Recognition (cs.CV)	Rishabh Goyal, Joaquin Vanschoren, Victor van Acht, Stephan Nijssen
2102.02167	The Instability of Accelerated Gradient Descent	Machine Learning (cs.LG)	Amit Attia, Tomer Koren
2102.02804	A Deeper Look into Convolutions via Pruning	Computer Vision and Pattern Recognition (cs.CV)	Ilke Cugu, Emre Akbas
2102.02973	Show, Attend and Distill:Knowledge Distillation via Attention-based Feature Matching	Machine Learning (cs.LG)	Mingi Ji, Byeongho Heo, Sungrae Park
2102.03214	GNN-RL Compression: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning	Computer Vision and Pattern Recognition (cs.CV)	Sixing Yu, Arya Mazaheri, Ali Jannesari
2102.03700	A procedure for automated tree pruning suggestion using LiDAR scans of fruit trees	Computer Vision and Pattern Recognition (cs.CV)	Fredrik Westling, James Underwood, Mitch Bryson
2102.03926	Lower Bounds and Accelerated Algorithms for Bilevel Optimization	Machine Learning (cs.LG)	Kaiyi Ji, Yingbin Liang
2102.03986	DEFT: Distilling Entangled Factors	Machine Learning (cs.LG)	Jiantao Wu, Lin Wang, Chunxiuzi Liu
2102.04487	Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning	Machine Learning (cs.LG)	Divyansh Jhunjhunwala, Advait Gadhikar, Gauri Joshi, Yonina C. Eldar
2102.04503	VS-Quant: Per-vector Scaled Quantization for Accurate Low-Precision Neural Network Inference	Machine Learning (cs.LG)	Steve Dai, Rangharajan Venkatesan, Haoxing Ren, Brian Zimmer, William J. Dally, Brucek Khailany
2102.04761	Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data	Machine Learning (cs.LG)	Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi
2102.04782	Distribution Adaptive INT8 Quantization for Training CNNs	Computer Vision and Pattern Recognition (cs.CV)	Kang Zhao, Sida Huang, Pan Pan, Yinghan Li, Yingya Zhang, Zhenyu Gu, Yinghui Xu
2102.04887	NewsBERT: Distilling Pre-trained Language Model for Intelligent News Application	Computation and Language (cs.CL)	Chuhan Wu, Fangzhao Wu, Yang Yu, Tao Qi, Yongfeng Huang, Qi Liu
2102.05221	Early Abandoning and Pruning for Elastic Distances	Machine Learning (cs.LG)	Matthieu Herrmann, Geoffrey I. Webb
2102.05426	BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction	Machine Learning (cs.LG)	Yuhang Li, Ruihao Gong, Xu Tan, Yang Yang, Peng Hu, Qi Zhang, Fengwei Yu, Wei Wang, Shi Gu
2102.05437	Pruning of Convolutional Neural Networks Using Ising Energy Model	Neural and Evolutionary Computing (cs.NE)	Hojjat Salehinejad, Shahrokh Valaee
2102.06024	Feature Selection for Multivariate Time Series via Network Pruning	Machine Learning (cs.LG)	Kang Gu, Soroush Vosoughi, Temiloluwa Prioleau
2102.06035	A Continuized View on Nesterov Acceleration	Distributed, Parallel, and Cluster Computing (cs.DC)	Raphaël Berthier (PSL, SIERRA), Francis Bach (SIERRA, PSL), Nicolas Flammarion, Pierre Gaillard (UGA), Adrien Taylor (SIERRA, PSL)
2102.06366	Confounding Tradeoffs for Neural Network Quantization	Machine Learning (cs.LG)	Sahaj Garg, Anirudh Jain, Joe Lou, Mitchell Nahmias
2102.06849	Distilling Double Descent	Machine Learning (cs.LG)	Andrew Cotter, Aditya Krishna Menon, Harikrishna Narasimhan, Ankit Singh Rawat, Sashank J. Reddi, Yichen Zhou
2102.07071	Doping: A technique for efficient compression of LSTM models using sparse structured additive matrices	Machine Learning (cs.LG)	Urmish Thakker, Paul N. Whatmough, Zhigang Liu, Matthew Mattina, Jesse Beu
2102.07125	Self Regulated Learning Mechanism for Data Efficient Knowledge Distillation	Machine Learning (cs.LG)	Sourav Mishra, Suresh Sundaram
2102.07142	Distillation based Multi-task Learning: A Candidate Generation Model for Improving Reading Duration	Information Retrieval (cs.IR)	Zhong Zhao, Yanmei Fu, Hanming Liang, Li Ma, Guangyao Zhao, Hongwei Jiang
2102.07143	Manifold Density Estimation via Generalized Dequantization	Machine Learning (stat.ML)	James A. Brofos, Marcus A. Brubaker, Roy R. Lederman
2102.07156	ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations	Computer Vision and Pattern Recognition (cs.CV)	Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak K. Gupta
2102.07219	Error-driven Pruning of Language Models for Virtual Assistants	Computation and Language (cs.CL)	Sashank Gondala, Lyan Verwimp, Ernest Pusateri, Manos Tsagkias, Christophe Van Gysel
2102.07245	Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization	Machine Learning (cs.LG)	Mher Safaryan, Filip Hanzely, Peter Richtárik
2102.07402	Compression phase is not necessary for generalization in representation learning	Machine Learning (cs.LG)	Sungyeop Lee, Junghyo Jo
2102.07631	Accelerating COVID-19 research with graph mining and transformer-based learning	Information Retrieval (cs.IR)	Ilya Tyagin, Ankit Kulshrestha, Justin Sybrandt, Krish Matta, Michael Shtutman, Ilya Safro
2102.07635	Improved Customer Transaction Classification using Semi-Supervised Knowledge Distillation	Computation and Language (cs.CL)	Rohan Sukumaran
2102.07650	Learning Student-Friendly Teacher Networks for Knowledge Distillation	Machine Learning (cs.LG)	Dae Young Park, Moon-Hyun Cha, Changwook Jeong, Daesin Kim, Bohyung Han
2102.07725	Neural Network Compression for Noisy Storage Devices	Machine Learning (cs.LG)	Berivan Isik, Kristy Choi, Xin Zheng, Tsachy Weissman, Stefano Ermon, H.-S. Philip Wong, Armin Alaghi
2102.07804	Scaling Up Exact Neural Network Compression by ReLU Stability	Machine Learning (cs.LG)	Thiago Serra, Abhinav Kumar, Srikumar Ramalingam
2102.07845	MARINA: Faster Non-Convex Distributed Learning with Compression	Machine Learning (cs.LG)	Eduard Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtárik
2102.07935	Hierarchical Transformer-based Large-Context End-to-end ASR with Large-Context Knowledge Distillation	Computation and Language (cs.CL)	Ryo Masumura, Naoki Makishima, Mana Ihori, Akihiko Takashima, Tomohiro Tanaka, Shota Orihashi
2102.07981	SiMaN: Sign-to-Magnitude Network Binarization	Computer Vision and Pattern Recognition (cs.CV)	Mingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang, Fei Chao, Mingliang Xu, Chia-Wen Lin, Ling Shao
2102.08124	Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N:M Transposable Masks	Artificial Intelligence (cs.AI)	Itay Hubara, Brian Chmiel, Moshe Island, Ron Banner, Seffi Naor, Daniel Soudry
2102.08329	Successive Pruning for Model Compression via Rate Distortion Theory	Machine Learning (cs.LG)	Berivan Isik, Albert No, Tsachy Weissman
2102.08374	IntSGD: Floatless Compression of Stochastic Gradients	Machine Learning (cs.LG)	Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev, Peter Richtárik
2102.08893	An Implementation of Vector Quantization using the Genetic Algorithm Approach	Neural and Evolutionary Computing (cs.NE)	Maha Mohammed Khan
2102.10335	Exploring Knowledge Distillation of a Deep Neural Network for Multi-Script identification	Computer Vision and Pattern Recognition (cs.CV)	Shuvayan Ghosh Dastidar, Kalpita Dutta, Nibaran Das, Mahantapas Kundu, Mita Nasipuri
2102.10462	BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization	Machine Learning (cs.LG)	Huanrui Yang, Lin Duan, Yiran Chen, Hai Li
2102.10697	Pruning the Index Contents for Memory Efficient Open-Domain QA	Computation and Language (cs.CL)	Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz
2102.10711	Accelerated Sim-to-Real Deep Reinforcement Learning: Learning Collision Avoidance from Human Player	Artificial Intelligence (cs.AI)	Hanlin Niu, Ze Ji, Farshad Arvin, Barry Lennox, Hujun Yin, Joaquin Carrasco
2102.10760	Unsupervised Meta Learning for One Shot Title Compression in Voice Commerce	Machine Learning (cs.LG)	Snehasish Mukherjee
2102.10780	Multi-View Feature Representation for Dialogue Generation with Bidirectional Distillation	Computation and Language (cs.CL)	Shaoxiong Feng, Xuancheng Ren, Kan Li, Xu Sun
2102.11086	Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding	Machine Learning (cs.LG)	Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison
2102.11221	Mixed-Precision Quantization and Parallel Implementation of Multispectral Riemannian Classification for Brain--Machine Interfaces	Signal Processing (eess.SP)	Xiaying Wang, Tibor Schneider, Michael Hersche, Lukas Cavigelli, Luca Benini
2102.11289	Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference	Machine Learning (cs.LG)	Benjamin Hawks, Javier Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu
2102.11545	Accelerating Recursive Partition-Based Causal Structure Learning	Machine Learning (cs.LG)	Md. Musfiqur Rahman, Ayman Rasheed, Md. Mosaddek Khan, Mohammad Ali Javidian, Pooyan Jamshidi, Md. Mamun-Or-Rashid
2102.11638	Enhancing Data-Free Adversarial Distillation with Activation Regularization and Virtual Interpolation	Machine Learning (cs.LG)	Xiaoyang Qu, Jianzong Wang, Jing Xiao
2102.12132	Quantitative Evaluation of Crack Depths on Thin Aluminum Plate using Eddy Current Pulse-Compression Thermography	Signal Processing (eess.SP)	Qiuji Yi, Hamed Malekmohammadi, Gui Yun Tian, Stefano Laureti, Marco Ricci
2102.12252	Localization Distillation for Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Zhaohui Zheng, Rongguang Ye, Ping Wang, Jun Wang, Dongwei Ren, Wangmeng Zuo
2102.12528	Preserved central model for faster bidirectional compression in distributed settings	Machine Learning (cs.LG)	Constantin Philippenko, Aymeric Dieuleveut
2102.12731	Improving Approximate Optimal Transport Distances using Quantization	Machine Learning (cs.LG)	Gaspard Beugnot, Aude Genevay, Kristjan Greenewald, Justin Solomon
2102.12817	Fronthaul Compression and Passive Beamforming Design for Intelligent Reflecting Surface-aided Cloud Radio Access Networks	Signal Processing (eess.SP)	Yu Zhang, Xuelu Wu, Hong Peng, Caijun Zhong, Xiaoming Chen
2102.12936	Risk factor identification for incident heart failure using neural network distillation and variable selection	Machine Learning (cs.LG)	Yikuan Li, Shishir Rao, Mohammad Mamouei, Gholamreza Salimi-Khorshidi, Dexter Canoy, Abdelaali Hassaine, Thomas Lukasiewicz, Kazem Rahimi
2102.13079	Quantization Algorithms for Random Fourier Features	Machine Learning (stat.ML)	Xiaoyun Li, Ping Li
2102.13088	Even your Teacher Needs Guidance: Ground-Truth Targets Dampen Regularization Imposed by Self-Distillation	Machine Learning (cs.LG)	Kenneth Borup, Lars N. Andersen
2102.13188	A Framework For Pruning Deep Neural Networks Using Energy-Based Models	Neural and Evolutionary Computing (cs.NE)	Hojjat Salehinejad, Shahrokh Valaee
2102.13323	Knowledge Distillation Circumvents Nonlinearity for Optical Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Jinlin Xiang, Shane Colburn, Arka Majumdar, Eli Shlizerman
2103.00053	PURSUhInT: In Search of Informative Hint Points Based on Layer Clustering for Knowledge Distillation	Machine Learning (cs.LG)	Reyhan Kevser Keser, Aydin Ayanzadeh, Omid Abdollahi Aghdam, Caglar Kilcioglu, Behcet Ugur Toreyin, Nazim Kemal Ure
2103.00422	Alignment Knowledge Distillation for Online Streaming Attention-based Speech Recognition	Audio and Speech Processing (eess.AS)	Hirofumi Inaguma, Tatsuya Kawahara
2103.00497	Distilling Knowledge via Intermediate Classifier Heads	Machine Learning (cs.LG)	Aryan Asadian, Amirali Salehi-Abari
2103.00543	On the Utility of Gradient Compression in Distributed Training Systems	Distributed, Parallel, and Cluster Computing (cs.DC)	Saurabh Agarwal, Hongyi Wang, Shivaram Venkataraman, Dimitris Papailiopoulos
2103.00793	Embedded Knowledge Distillation in Depth-level Dynamic Neural Network	Computer Vision and Pattern Recognition (cs.CV)	Shuchang Lyu, Ting-Bing Xu, Guangliang Cheng
2103.01049	Diversifying Sample Generation for Accurate Data-Free Quantization	Computer Vision and Pattern Recognition (cs.CV)	Xiangguo Zhang, Haotong Qin, Yifu Ding, Ruihao Gong, Qinghua Yan, Renshuai Tao, Yuhang Li, Fengwei Yu, Xianglong Liu
2103.01114	Deep Perceptual Image Quality Assessment for Compression	Computer Vision and Pattern Recognition (cs.CV)	Juan Carlos Mier, Eddie Huang, Hossein Talebi, Feng Yang, Peyman Milanfar
2103.01304	Accelerating Distributed-Memory Autotuning via Statistical Analysis of Execution Paths	Distributed, Parallel, and Cluster Computing (cs.DC)	Edward Hutter, Edgar Solomonik
2103.01308	SWIS -- Shared Weight bIt Sparsity for Efficient Neural Network Acceleration	Machine Learning (cs.LG)	Shurui Li, Wojciech Romaszkan, Alexander Graening, Puneet Gupta
2103.01338	Acceleration via Fractal Learning Rate Schedules	Machine Learning (cs.LG)	Naman Agarwal, Surbhi Goel, Cyril Zhang
2103.01353	There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge	Computer Vision and Pattern Recognition (cs.CV)	Francisco Rivera Valverde, Juana Valeria Hurtado, Abhinav Valada
2103.01435	All at Once Network Quantization via Collaborative Knowledge Transfer	Computer Vision and Pattern Recognition (cs.CV)	Ximeng Sun, Rameswar Panda, Chun-Fu Chen, Naigang Wang, Bowen Pan Kailash Gopalakrishnan, Aude Oliva, Rogerio Feris, Kate Saenko
2103.01542	TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning	Computer Vision and Pattern Recognition (cs.CV)	Bingyan Liu, Yifeng Cai, Yao Guo, Xiangqun Chen
2103.01594	Probing Product Description Generation via Posterior Distillation	Computation and Language (cs.CL)	Haolan Zhan, Hainan Zhang, Hongshen Chen, Lei Shen, Zhuoye Ding, Yongjun Bao, Weipeng Yan, Yanyan Lan
2103.01737	Distilling Causal Effect of Data in Class-Incremental Learning	Artificial Intelligence (cs.AI)	Xinting Hu, Kaihua Tang, Chunyan Miao, Xian-Sheng Hua, Hanwang Zhang
2103.01847	Network Pruning via Resource Reallocation	Computer Vision and Pattern Recognition (cs.CV)	Yuenan Hou, Zheng Ma, Chunxiao Liu, Zhe Wang, Chen Change Loy
2103.02087	Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization	Signal Processing (eess.SP)	Marius Arvinte, Sriram Vishwanath, Ahmed H. Tewfik, Jonathan I. Tamir
2103.02340	General Instance Distillation for Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Xing Dai, Zeren Jiang, Zhao Wu, Yiping Bao, Zhicheng Wang, Si Liu, Erjin Zhou
2103.02843	Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers	Distributed, Parallel, and Cluster Computing (cs.DC)	Agastya P. Bhati, Shunzhou Wan, Dario Alfè, Austin R. Clyde, Mathis Bode, Li Tan, Mikhail Titov, Andre Merzky, Matteo Turilli, Shantenu Jha, Roger R. Highfield, Walter Rocchia, Nicola Scafuri, Sauro Succi, Dieter Kranzlmüller, Gerald Mathias, David Wifling, Yann Donon, Alberto Di Meglio, Sofia Vallecorsa, Heng Ma, Anda Trifan, Arvind Ramanathan, Tom Brettin, Alexander Partin, Fangfang Xia, Xiaotan Duan, Rick Stevens, Peter V. Coveney
2103.02885	Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework	Machine Learning (cs.LG)	Cheng Yang, Jiawei Liu, Chuan Shi
2103.02889	Efficient Training Convolutional Neural Networks on Edge Devices with Gradient-pruned Sign-symmetric Feedback Alignment	Machine Learning (cs.LG)	Ziyang Hong, C. Patrick Yue
2103.02904	Effective and Fast: A Novel Sequential Single Path Search for Mixed-Precision Quantization	Computer Vision and Pattern Recognition (cs.CV)	Qigong Sun, Licheng Jiao, Yan Ren, Xiufang Li, Fanhua Shang, Fang Liu
2103.03014	Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy	Machine Learning (cs.LG)	Lucas Liebenwein, Cenk Baykal, Brandon Carter, David Gifford, Daniela Rus
2103.03387	PolarNet: Accelerated Deep Open Space Segmentation Using Automotive Radar in Polar Domain	Computer Vision and Pattern Recognition (cs.CV)	Farzan Erlik Nowruzi, Dhanvin Kolhatkar, Prince Kapoor, Elnaz Jahani Heravi, Fahed Al Hassanat, Robert Laganiere, Julien Rebut, Waqas Malik
2103.03467	Teachers Do More Than Teach: Compressing Image-to-Image Models	Computer Vision and Pattern Recognition (cs.CV)	Qing Jin, Jian Ren, Oliver J. Woodford, Jiazhuo Wang, Geng Yuan, Yanzhi Wang, Sergey Tulyakov
2103.04039	ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic	Computer Vision and Pattern Recognition (cs.CV)	Xiangtao Kong, Hengyuan Zhao, Yu Qiao, Chao Dong
2103.04059	Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning	Computer Vision and Pattern Recognition (cs.CV)	Ali Cheraghian, Shafin Rahman, Pengfei Fang, Soumava Kumar Roy, Lars Petersson, Mehrtash Harandi
2103.04062	Adaptive Multi-Teacher Multi-level Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yuang Liu, Wei Zhang, Jun Wang
2103.04559	Parser-Free Virtual Try-on via Distilling Appearance Flows	Computer Vision and Pattern Recognition (cs.CV)	Yuying Ge, Yibing Song, Ruimao Zhang, Chongjian Ge, Wei Liu, Ping Luo
2103.04764	Neural Network-based Quantization for Network Automation	Machine Learning (cs.LG)	Marton Kajo, Stephen S. Mwanje, Benedek Schultz, Georg Carle
2103.05861	Manifold Regularized Dynamic Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Yehui Tang, Yunhe Wang, Yixing Xu, Yiping Deng, Chao Xu, Dacheng Tao, Chang Xu
2103.05959	Beyond Self-Supervision: A Simple Yet Effective Network Distillation Alternative to Improve Backbones	Computer Vision and Pattern Recognition (cs.CV)	Cheng Cui, Ruoyu Guo, Yuning Du, Dongliang He, Fu Li, Zewu Wu, Qiwen Liu, Shilei Wen, Jizhou Huang, Xiaoguang Hu, Dianhai Yu, Errui Ding, Yanjun Ma
2103.06002	Robustness to Pruning Predicts Generalization in Deep Neural Networks	Machine Learning (cs.LG)	Lorenz Kuhn, Clare Lyle, Aidan N. Gomez, Jonas Rothfuss, Yarin Gal
2103.06123	The whole brain architecture approach: Accelerating the development of artificial general intelligence by referring to the brain	Artificial Intelligence (cs.AI)	Hiroshi Yamakawa
2103.06231	Quantization-Guided Training for Compact TinyML Models	Machine Learning (cs.LG)	Sedigh Ghamari, Koray Ozcan, Thu Dinh, Andrey Melnikov, Juan Carvajal, Jan Ernst, Sek Chai
2103.06418	LightMBERT: A Simple Yet Effective Method for Multilingual BERT Distillation	Computation and Language (cs.CL)	Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, Qun Liu
2103.06460	Emerging Paradigms of Neural Network Pruning	Machine Learning (cs.LG)	Huan Wang, Can Qin, Yulun Zhang, Yun Fu
2103.06523	Improving Bi-encoder Document Ranking Models with Two Rankers and Multi-teacher Distillation	Information Retrieval (cs.IR)	Jaekeol Choi, Euna Jung, Jangwon Suh, Wonjong Rhee
2103.07156	Learnable Companding Quantization for Accurate Low-bit Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Kohei Yamamoto
2103.07362	PLADE-Net: Towards Pixel-Level Accuracy for Self-Supervised Single-View Depth Estimation with Neural Positional Encoding and Distilled Matting Loss	Computer Vision and Pattern Recognition (cs.CV)	Juan Luis Gonzalez Bello, Munchurl Kim
2103.07668	Robust Model Compression Using Deep Hypotheses	Machine Learning (cs.LG)	Omri Armstrong, Ran Gilad-Bachrach
2103.07790	A Few-Shot Learning Approach for Accelerated MRI via Fusion of Data-Driven and Subject-Driven Priors	Computer Vision and Pattern Recognition (cs.CV)	Salman Ul Hassan Dar, Mahmut Yurt, Tolga Çukur
2103.08273	Refine Myself by Teaching Myself: Feature Refinement via Self-Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Mingi Ji, Seungjae Shin, Seunghyun Hwang, Gibeom Park, Il-Chul Moon
2103.08397	Metric Learning for Anti-Compression Facial Forgery Detection	Computer Vision and Pattern Recognition (cs.CV)	Shenhao Cao, Qin Zou, Xiuqing Mao, Zhongyuan Wang
2103.08457	RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs	Computer Vision and Pattern Recognition (cs.CV)	Zhiwei Xu, Thalaiyasingam Ajanthan, Vibhav Vineet, Richard Hartley
2103.08765	Data Discovery Using Lossless Compression-Based Sparse Representation	Signal Processing (eess.SP)	Elyas Sabeti, Peter X.K. Song, Alfred O. Hero III
2103.08809	Robustly Optimized and Distilled Training for Natural Language Understanding	Computation and Language (cs.CL)	Haytham ElFadeel, Stan Peshterliev
2103.08870	Learned Gradient Compression for Distributed Deep Learning	Machine Learning (cs.LG)	Lusine Abrahamyan, Yiming Chen, Giannis Bekoulis, Nikos Deligiannis
2103.09136	QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Chenhongyi Yang, Zehao Huang, Naiyan Wang
2103.09377	Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network	Machine Learning (cs.LG)	James Diffenderfer, Bhavya Kailkhura
2103.09683	Accelerating Radiation Therapy Dose Calculation with Nvidia GPUs	Distributed, Parallel, and Cluster Computing (cs.DC)	Felix Liu, Niclas Jansson, Artur Podobas, Albin Fredriksson, Stefano Markidis
2103.09903	Transformer-based ASR Incorporating Time-reduction Layer and Fine-tuning with Self-Knowledge Distillation	Artificial Intelligence (cs.AI)	Md Akmal Haidar, Chao Xing, Mehdi Rezagholizadeh
2103.10047	Similarity Transfer for Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Haoran Zhao, Kun Gong, Xin Sun, Junyu Dong, Hui Yu
2103.10051	Data-free mixed-precision quantization using novel sensitivity metric	Machine Learning (cs.LG)	Donghyun Lee, Minkyoung Cho, Seungwon Lee, Joonho Song, Changkyu Choi
2103.10150	Lossless compression with state space models using bits back coding	Machine Learning (cs.LG)	James Townsend, Iain Murray
2103.10559	CDFI: Compression-Driven Network Design for Frame Interpolation	Computer Vision and Pattern Recognition (cs.CV)	Tianyu Ding, Luming Liang, Zhihui Zhu, Ilya Zharkov
2103.10629	Cascade Weight Shedding in Deep Neural Networks: Benefits and Pitfalls for Network Pruning	Machine Learning (cs.LG)	Kambiz Azarian, Fatih Porikli
2103.10858	Toward Compact Deep Neural Networks via Energy-Aware Pruning	Computer Vision and Pattern Recognition (cs.CV)	Seul-Ki Yeom, Kyung-Hwan Shim, Jee-Hyun Hwang
2103.10891	Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More	Machine Learning (cs.LG)	Shabnam Daghaghi, Nicholas Meisburger, Mengnan Zhao, Yong Wu, Sameh Gobriel, Charlie Tai, Anshumali Shrivastava
2103.11109	DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation	Machine Learning (cs.LG)	Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li
2103.11367	ROSITA: Refined BERT cOmpreSsion with InTegrAted techniques	Computation and Language (cs.CL)	Yuanxin Liu, Zheng Lin, Fengcheng Yuan
2103.11704	n-hot: Efficient bit-level sparsity for powers-of-two neural network quantization	Computer Vision and Pattern Recognition (cs.CV)	Yuiko Sakuma, Hiroshi Sumihiro, Jun Nishikawa, Toshiki Nakamura, Ryoji Ikegaya
2103.11864	Recovery of Joint Probability Distribution from one-way marginals: Low rank Tensors and Random Projections	Machine Learning (cs.LG)	Jian Vora, Karthik S. Gurumoorthy, Ajit Rajwade
2103.11912	Evaluating Post-Training Compression in GANs using Locality-Sensitive Hashing	Machine Learning (cs.LG)	Gonçalo Mordido, Haojin Yang, Christoph Meinel
2103.12388	Joint Weakly Supervised AT and AED Using Deep Feature Distillation and Adaptive Focal Loss	Audio and Speech Processing (eess.AS)	Yunhao Liang, Yanhua Long, Yijie Li, Jiaen Liang
2103.12868	A High-order Tuner for Accelerated Learning and Control	Machine Learning (cs.LG)	Spencer McDonald, Yingnan Cui, Joseph E. Gaudio, Anuradha M. Annaswamy
2103.12992	Non-Compression Auto-Encoder for Detecting Road Surface Abnormality via Vehicle Driving Noise	Computer Vision and Pattern Recognition (cs.CV)	YeongHyeon Park, JongHee Jung
2103.13322	DNN Quantization with Attention	Computer Vision and Pattern Recognition (cs.CV)	Ghouthi Boukli Hacene, Lukas Mauch, Stefan Uhlich, Fabien Cardinaux
2103.13630	A Survey of Quantization Methods for Efficient Neural Network Inference	Computer Vision and Pattern Recognition (cs.CV)	Amir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer
2103.13678	Pruning-then-Expanding Model for Domain Adaptation of Neural Machine Translation	Computation and Language (cs.CL)	Shuhao Gu, Yang Feng, Wanying Xie
2103.13733	Spirit Distillation: Precise Real-time Prediction with Insufficient Data	Computer Vision and Pattern Recognition (cs.CV)	Zhiyuan Wu, Hong Qi, Yu Jiang, Chupeng Cui, Zongmin Yang, Xinhui Xue
2103.13811	Student Network Learning via Evolutionary Knowledge Distillation	Machine Learning (cs.LG)	Kangkai Zhang, Chunhui Zhang, Shikun Li, Dan Zeng, Shiming Ge
2103.13941	SMILE: Self-Distilled MIxup for Efficient Transfer LEarning	Machine Learning (cs.LG)	Xingjian Li, Haoyi Xiong, Chengzhong Xu, Dejing Dou
2103.14337	Hands-on Guidance for Distilling Object Detectors	Computer Vision and Pattern Recognition (cs.CV)	Yangyang Qin, Hefei Ling, Zhenghai He, Yuxuan Shi, Lei Wu
2103.14473	Distilling a Powerful Student Model via Online Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Shaojie Li, Mingbao Lin, Yan Wang, Feiyue Huang, Yongjian Wu, Yonghong Tian, Ling Shao, Rongrong Ji
2103.14475	Distilling Object Detectors via Decoupled Features	Computer Vision and Pattern Recognition (cs.CV)	Jianyuan Guo, Kai Han, Yunhe Wang, Han Wu, Xinghao Chen, Chunjing Xu, Chang Xu
2103.14496	Weakly-Supervised Domain Adaptation of Deep Regression Trackers via Reinforced Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Matteo Dunnhofer, Niki Martinel, Christian Micheloni
2103.14891	KnowRU: Knowledge Reusing via Knowledge Distillation in Multi-agent Reinforcement Learning	Artificial Intelligence (cs.AI)	Zijian Gao, Kele Xu, Bo Ding, Huaimin Wang, Yiying Li, Hongda Jia
2103.14949	Automated Backend-Aware Post-Training Quantization	Computer Vision and Pattern Recognition (cs.CV)	Ziheng Jiang, Animesh Jain, Andrew Liu, Josh Fromm, Chengqian Ma, Tianqi Chen, Luis Ceze
2103.15042	Distilling Virtual Examples for Long-tailed Recognition	Computer Vision and Pattern Recognition (cs.CV)	Yin-Yin He, Jianxin Wu, Xiu-Shen Wei
2103.15195	MergeComp: A Compression Scheduler for Scalable Communication-Efficient Distributed Training	Distributed, Parallel, and Cluster Computing (cs.DC)	Zhuang Wang, Xinyu Wu, T.S. Eugene Ng
2103.15263	Zero-shot Adversarial Quantization	Computer Vision and Pattern Recognition (cs.CV)	Yuang Liu, Wei Zhang, Jun Wang
2103.15564	Prototype-based Personalized Pruning	Machine Learning (cs.LG)	Jangho Kim, Simyung Chang, Sungrack Yun, Nojun Kwak
2103.15851	Distilled Replay: Overcoming Forgetting through Synthetic Samples	Machine Learning (cs.LG)	Andrea Rosasco, Antonio Carta, Andrea Cossu, Vincenzo Lomonaco, Davide Bacciu
2103.15972	Deep Compression for PyTorch Model Deployment on Microcontrollers	Machine Learning (cs.LG)	Eren Dogan, H. Fatih Ugurdag, Hasan Unlu
2103.16211	iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compression	Machine Learning (cs.LG)	Shifeng Zhang, Chen Zhang, Ning Kang, Li Zhenguo
2103.16367	Complementary Relation Contrastive Distillation	Computer Vision and Pattern Recognition (cs.CV)	Jinguo Zhu, Shixiang Tang, Dapeng Chen, Shijie Yu, Yakun Liu, Aijun Yang, Mingzhe Rong, Xiaohua Wang
2103.16700	Trees, Forests, Chickens, and Eggs: When and Why to Prune Trees in a Random Forest	Machine Learning (stat.ML)	Siyu Zhou, Lucas Mentch
2103.16844	Fixing the Teacher-Student Knowledge Discrepancy in Distillation	Computer Vision and Pattern Recognition (cs.CV)	Jiangfan Han, Mengya Gao, Yujie Wang, Quanquan Li, Hongsheng Li, Xiaogang Wang
2103.17012	Knowledge Distillation By Sparse Representation Matching	Computer Vision and Pattern Recognition (cs.CV)	Dat Thanh Tran, Moncef Gabbouj, Alexandros Iosifidis
2103.17115	Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Hanzhe Hu, Shuai Bai, Aoxue Li, Jinshi Cui, Liwei Wang
2103.17142	Compressing 1D Time-Channel Separable Convolutions using Sparse Random Ternary Matrices	Machine Learning (cs.LG)	Gonçalo Mordido, Matthijs Van keirsbilck, Alexander Keller
2104.00178	Adaptive Configuration of In Situ Lossy Compression for Cosmology Simulations via Fine-Grained Rate-Quality Modeling	Distributed, Parallel, and Cluster Computing (cs.DC)	Sian Jin, Jesus Pulido, Pascal Grosset, Jiannan Tian, Dingwen Tao, James Ahrens
2104.00179	Selective Feature Compression for Efficient Activity Recognition Inference	Computer Vision and Pattern Recognition (cs.CV)	Chunhui Liu, Xinyu Li, Hao Chen, Davide Modolo, Joseph Tighe
2104.00185	Less is More: Accelerating Faster Neural Networks Straight from JPEG	Computer Vision and Pattern Recognition (cs.CV)	Samuel Felipe dos Santos, Jurandy Almeida
2104.00189	Dealing with CSI Compression to Reduce Losses and Overhead: An Artificial Intelligence Approach	Signal Processing (eess.SP)	Muhammad Karam Shehzad, Luca Rose, Mohamad Assaad
2104.00222	Embedded Self-Distillation in Compact Multi-Branch Ensemble Network for Remote Sensing Scene Classification	Computer Vision and Pattern Recognition (cs.CV)	Qi Zhao, Yujing Ma, Shuchang Lyu, Lijiang Chen
2104.00299	Students are the Best Teacher: Exit-Ensemble Distillation with Multi-Exits	Computer Vision and Pattern Recognition (cs.CV)	Hojung Lee, Jong-Seok Lee
2104.00432	Anchor Pruning for Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Maxim Bonnaerens, Matthias Freiberger, Joni Dambre
2104.00664	Sampling and Filtering of Neural Machine Translation Distillation Data	Computation and Language (cs.CL)	Vilém Zouhar
2104.00676	Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study	Machine Learning (cs.LG)	Zhiqiang Shen, Zechun Liu, Dejia Xu, Zitian Chen, Kwang-Ting Cheng, Marios Savvides
2104.00788	A study on the effects of compression on hyperspectral image classification	Computer Vision and Pattern Recognition (cs.CV)	Kiran Mantripragada, Phuong D. Dao, Yuhong He, Faisal Z. Qureshi
2104.00875	Half-Real Half-Fake Distillation for Class-Incremental Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Zilong Huang, Wentian Hao, Xinggang Wang, Mingyuan Tao, Jianqiang Huang, Wenyu Liu, Xian-Sheng Hua
2104.00903	Network Quantization with Element-wise Gradient Scaling	Computer Vision and Pattern Recognition (cs.CV)	Junghyup Lee, Dohyung Kim, Bumsub Ham
2104.01188	Scan Specific Artifact Reduction in K-space (SPARK) Neural Networks Synergize with Physics-based Reconstruction to Accelerate MRI	Signal Processing (eess.SP)	Yamin Arefeen (1), Onur Beker (2), Jaejin Cho (3), Heng Yu (4), Elfar Adalsteinsson (1 and 5 and 6), Berkin Bilgic (3 and 5 and 7) ((1) Massachusetts Institute of Technology, (2) École Polytechnique Fédérale de Lausanne, (3) Athinoula A. Martinos Center for Biomedical Imaging (4) Tsinghua University, (5) Harvard-MIT Health Sciences and Technology, (6) Institute for Medical Engineering and Science, (7) Harvard Medical School)
2104.01303	Tight Compression: Compressing CNN Through Fine-Grained Pruning and Weight Permutation for Efficient Implementation	Machine Learning (cs.LG)	Xizi Chen, Jingyang Zhu, Jingbo Jiang, Chi-Ying Tsui
2104.01353	Deepfake Detection Scheme Based on Vision Transformer and Distillation	Computer Vision and Pattern Recognition (cs.CV)	Young-Jin Heo, Young-Ju Choi, Young-Woon Lee, Byung-Gyu Kim
2104.01539	Distill and Fine-tune: Effective Adaptation from a Black-box Source Model	Computer Vision and Pattern Recognition (cs.CV)	Jian Liang, Dapeng Hu, Ran He, Jiashi Feng
2104.01655	Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation	Machine Learning (cs.LG)	Emilio Parisotto, Ruslan Salakhutdinov
2104.01730	Branch-and-Pruning Optimization Towards Global Optimality in Deep Learning	Computer Vision and Pattern Recognition (cs.CV)	Yuanwei Wu, Ziming Zhang, Guanghui Wang
2104.01830	Model Compression for Dynamic Forecast Combination	Machine Learning (stat.ML)	Vitor Cerqueira, Luis Torgo, Carlos Soares, Albert Bifet
2104.02041	Exploring Transformers in Emotion Recognition: a comparison of BERT, DistillBERT, RoBERTa, XLNet and ELECTRA	Computation and Language (cs.CL)	Diogo Cortiz
2104.02096	Compressing Visual-linguistic Model via Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Zhiyuan Fang, Jianfeng Wang, Xiaowei Hu, Lijuan Wang, Yezhou Yang, Zicheng Liu
2104.02233	TENT: Efficient Quantization of Neural Networks on the tiny Edge with Tapered FixEd PoiNT	Machine Learning (cs.LG)	Hamed F. Langroudi, Vedant Karia, Tej Pandit, Dhireesha Kudithipudi
2104.02243	3D-to-2D Distillation for Indoor Scene Parsing	Computer Vision and Pattern Recognition (cs.CV)	Zhengzhe Liu, Xiaojuan Qi, Chi-Wing Fu
2104.02244	Content-Aware GAN Compression	Computer Vision and Pattern Recognition (cs.CV)	Yuchen Liu, Zhixin Shu, Yijun Li, Zhe Lin, Federico Perazzi, S.Y. Kung
2104.02281	Learnable Expansion-and-Compression Network for Few-shot Class-Incremental Learning	Computer Vision and Pattern Recognition (cs.CV)	Boyu Yang, Mingbao Lin, Binghao Liu, Mengying Fu, Chang Liu, Rongrong Ji, Qixiang Ye
2104.02322	Efficient Video Compression via Content-Adaptive Super-Resolution	Computer Vision and Pattern Recognition (cs.CV)	Mehrdad Khani, Vibhaalakshmi Sivaraman, Mohammad Alizadeh
2104.02621	How to Accelerate Capsule Convolutions in Capsule Networks	Artificial Intelligence (cs.AI)	Zhenhua Chen, Xiwen Li, Qian Lou, David Crandall
2104.02862	Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification	Computer Vision and Pattern Recognition (cs.CV)	Xudong Tian, Zhizhong Zhang, Shaohui Lin, Yanyun Qu, Yuan Xie, Lizhuang Ma
2104.02882	FSR: Accelerating the Inference Process of Transducer-Based Models by Applying Fast-Skip Regularization	Audio and Speech Processing (eess.AS)	Zhengkun Tian, Jiangyan Yi, Ye Bai, Jianhua Tao, Shuai Zhang, Zhengqi Wen
2104.03164	Distilling and Transferring Knowledge via cGAN-generated Samples for Image Classification and Regression	Computer Vision and Pattern Recognition (cs.CV)	Xin Ding, Yongwei Wang, Zuheng Xu, Z. Jane Wang, William J. Welch
2104.03305	Learned transform compression with optimized entropy encoding	Machine Learning (cs.LG)	Magda Gregorová, Marc Desaules, Alexandros Kalousis
2104.03308	Warp Consistency for Unsupervised Learning of Dense Correspondences	Computer Vision and Pattern Recognition (cs.CV)	Prune Truong, Martin Danelljan, Fisher Yu, Luc Van Gool
2104.03438	Convolutional Neural Network Pruning with Structural Redundancy Reduction	Computer Vision and Pattern Recognition (cs.CV)	Zi Wang, Chengcheng Li, Xiangyang Wang
2104.03597	GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference	Machine Learning (cs.LG)	Mahsa Ghorbani, Mojtaba Bahrami, Anees Kazi, Mahdieh SoleymaniBaghshah, Hamid R. Rabiee, Nassir Navab
2104.04726	A Novel Unified Model for Multi-exposure Stereo Coding Based on Low Rank Tucker-ALS and 3D-HEVC	Computer Vision and Pattern Recognition (cs.CV)	Mansi Sharma, Aditya Wadaskar
2104.04868	Data-Free Knowledge Distillation with Soft Targeted Transfer Set Synthesis	Machine Learning (cs.LG)	Zi Wang
2104.05188	Accelerating science with human versus alien artificial intelligences	Artificial Intelligence (cs.AI)	Jamshid Sourati, James Evans
2104.05279	Class-Balanced Distillation for Long-Tailed Visual Recognition	Computer Vision and Pattern Recognition (cs.CV)	Ahmet Iscen, André Araujo, Boqing Gong, Cordelia Schmid
2104.05382	Dual Discriminator Adversarial Distillation for Data-free Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Haoran Zhao, Xin Sun, Junyu Dong, Hui Yu, Huiyu Zhou
2104.05541	Optimizing the Whole-life Cost in End-to-end CNN Acceleration	Distributed, Parallel, and Cluster Computing (cs.DC)	Jiaqi Zhang, Xiangru Chen, Sandip Ray
2104.05588	Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO)	Machine Learning (cs.LG)	Daniel Coquelin, Charlotte Debus, Markus Götz, Fabrice von der Lehr, James Kahn, Martin Siggel, Achim Streit
2104.05641	Generalization bounds via distillation	Machine Learning (cs.LG)	Daniel Hsu, Ziwei Ji, Matus Telgarsky, Lan Wang
2104.05765	Cloud Big Data Mining and Analytics: Bringing Greenness and Acceleration in the Cloud	Distributed, Parallel, and Cluster Computing (cs.DC)	Hrishav Bakul Barua, Kartick Chandra Mondal
2104.05802	Efficient Optimal Transport Algorithm by Accelerated Gradient descent	Machine Learning (cs.LG)	Dongsheng An, Na Lei, Xianfeng Gu
2104.05930	Distilling Wikipedia mathematical knowledge into neural network models	Machine Learning (cs.LG)	Joanne T. Kim, Mikel Landajuela Larma, Brenden K. Petersen
2104.05965	Dealing with Missing Modalities in the Visual Question Answer-Difference Prediction Task through Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Jae Won Cho, Dong-Jin Kim, Jinsoo Choi, Yunjae Jung, In So Kweon
2104.06023	Communication Efficient Federated Learning with Adaptive Quantization	Distributed, Parallel, and Cluster Computing (cs.DC)	Yuzhu Mao, Zihao Zhao, Guangfeng Yan, Yang Liu, Tian Lan, Linqi Song, Wenbo Ding
2104.06214	BlockGNN: Towards Efficient GNN Acceleration Using Block-Circulant Weight Matrices	Artificial Intelligence (cs.AI)	Zhe Zhou, Bizhao Shi, Zhe Zhang, Yijin Guan, Guangyu Sun, Guojie Luo
2104.06457	Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation	Computation and Language (cs.CL)	Hirofumi Inaguma, Tatsuya Kawahara, Shinji Watanabe
2104.06685	BROADCAST: Reducing Both Stochastic and Compression Noise to Robustify Communication-Efficient Federated Learning	Machine Learning (cs.LG)	Heng Zhu, Qing Ling
2104.06719	Sentence Embeddings by Ensemble Distillation	Computation and Language (cs.CL)	Fredrik Carlsson Magnus Sahlgren
2104.07163	Annealing Knowledge Distillation	Computation and Language (cs.CL)	Aref Jafari, Mehdi Rezagholizadeh, Pranav Sharma, Ali Ghodsi
2104.07858	Search-oriented Differentiable Product Quantization	Computation and Language (cs.CL)	Shitao Xiao, Zheng Liu, Yingxia Shao, Defu Lian, Xing Xie
2104.08163	Finding Motifs in Knowledge Graphs using Compression	Machine Learning (stat.ML)	Peter Bloem
2104.08265	Evaluation of Portable Acceleration Solutions for LArTPC Simulation Using Wire-Cell Toolkit	Distributed, Parallel, and Cluster Computing (cs.DC)	Haiwang Yu, Zhihua Dong, Kyle Knoepfel, Meifeng Lin, Brett Viren, Kwangmin Yu
2104.08271	TEACHTEXT: CrossModal Generalized Distillation for Text-Video Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Ioana Croitoru, Simion-Vlad Bogolin, Yang Liu, Samuel Albanie, Marius Leordeanu, Hailin Jin, Andrew Zisserman
2104.08378	Accelerating Sparse Deep Neural Networks	Machine Learning (cs.LG)	Asit Mishra, Jorge Albericio Latorre, Jeff Pool, Darko Stosic, Dusan Stosic, Ganesh Venkatesh, Chong Yu, Paulius Micikevicius
2104.08448	Data Distillation for Text Classification	Computation and Language (cs.CL)	Yongqi Li, Wenjie Li
2104.08500	Vision Transformer Pruning	Computer Vision and Pattern Recognition (cs.CV)	Mingjian Zhu, Yehui Tang, Kai Han
2104.08675	Dual-View Distilled BERT for Sentence Embedding	Artificial Intelligence (cs.AI)	Xingyi Cheng
2104.08682	Rethinking Network Pruning -- under the Pre-train and Fine-tune Paradigm	Computation and Language (cs.CL)	Dongkuan Xu, Ian E.H. Yen, Jinxi Zhao, Zhibin Xiao
2104.08803	Consistent Accelerated Inference via Confident Adaptive Transformers	Computation and Language (cs.CL)	Tal Schuster, Adam Fisch, Tommi Jaakkola, Regina Barzilay
2104.08945	Data-Efficient Language-Supervised Zero-Shot Learning with Self-Distillation	Computer Vision and Pattern Recognition (cs.CV)	Ruizhe Cheng, Bichen Wu, Peizhao Zhang, Peter Vajda, Joseph E. Gonzalez
2104.09044	Distilling Knowledge via Knowledge Review	Computer Vision and Pattern Recognition (cs.CV)	Pengguang Chen, Shu Liu, Hengshuang Zhao, Jiaya Jia
2104.09124	DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning	Computer Vision and Pattern Recognition (cs.CV)	Yuting Gao, Jia-Xin Zhuang, Ke Li, Hao Cheng, Xiaowei Guo, Feiyue Huang, Rongrong Ji, Xing Sun
2104.09191	Compact CNN Structure Learning by Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Waqar Ahmed, Andrea Zunino, Pietro Morerio, Vittorio Murino
2104.09565	Accelerating key bioinformatics tasks 100-fold by improving memory access	Distributed, Parallel, and Cluster Computing (cs.DC)	Igor Sfiligoi, Daniel McDonald, Rob Knight
2104.09732	Knowledge Distillation as Semiparametric Inference	Machine Learning (stat.ML)	Tri Dao, Govinda M Kamath, Vasilis Syrgkanis, Lester Mackey
2104.09866	Distill on the Go: Online knowledge distillation in self-supervised learning	Computer Vision and Pattern Recognition (cs.CV)	Prashant Bhat, Elahe Arani, Bahram Zonooz
2104.09987	Differentiable Model Compression via Pseudo Quantization Noise	Machine Learning (stat.ML)	Alexandre Défossez, Yossi Adi, Gabriel Synnaeve
2104.10065	Learning-based Compression for Material and Texture Recognition	Computer Vision and Pattern Recognition (cs.CV)	Yingpeng Deng, Lina J. Karam
2104.10414	Orderly Dual-Teacher Knowledge Distillation for Lightweight Human Pose Estimation	Computer Vision and Pattern Recognition (cs.CV)	Zhong-Qiu Zhao, Yao Gao, Yuchen Ge, Weidong Tian
2104.10501	A Survey on Federated Learning and its Applications for Accelerating Industrial Internet of Things	Distributed, Parallel, and Cluster Computing (cs.DC)	Jiehan Zhou, Shouhua Zhang, Qinghua Lu, Wenbin Dai, Min Chen, Xin Liu, Susanna Pirttikangas, Yang Shi, Weishan Zhang, Enrique Herrera-Viedma
2104.10510	Balanced Knowledge Distillation for Long-tailed Learning	Computer Vision and Pattern Recognition (cs.CV)	Shaoyu Zhang, Chen Chen, Xiyuan Hu, Silong Peng
2104.10544	Lossless Compression with Latent Variable Models	Machine Learning (cs.LG)	James Townsend
2104.10716	Accelerating SpMM Kernel with Cache-First Edge Sampling for Graph Neural Networks	Machine Learning (cs.LG)	Chien-Yu Lin, Liang Luo, Luis Ceze
2104.10955	Distilling Audio-Visual Knowledge by Compositional Contrastive Learning	Computer Vision and Pattern Recognition (cs.CV)	Yanbei Chen, Yongqin Xian, A. Sophia Koepke, Ying Shan, Zeynep Akata
2104.11057	Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition	Computer Vision and Pattern Recognition (cs.CV)	Lie Ju, Xin Wang, Lin Wang, Tongliang Liu, Xin Zhao, Tom Drummond, Dwarikanath Mahapatra, Zongyuan Ge
2104.11125	ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training	Machine Learning (cs.LG)	Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan
2104.11295	On Geodesic Distances and Contextual Embedding Compression for Text Classification	Machine Learning (cs.LG)	Rishi Jha, Kai Mihata
2104.11385	In-Situ Assessment of Device-Side Compute Work for Dynamic Load Balancing in a GPU-Accelerated PIC Code	Distributed, Parallel, and Cluster Computing (cs.DC)	Michael E. Rowan, Axel Huebl, Kevin N. Gott, Jack Deslippe, Maxence Thévenet, Remi Lehe, Jean-Luc Vay
2104.11471	tcFFT: Accelerating Half-Precision FFT through Tensor Cores	Distributed, Parallel, and Cluster Computing (cs.DC)	Binrui Li, Shenggan Cheng, James Lin
2104.11849	Do All MobileNets Quantize Poorly? Gaining Insights into the Effect of Quantization on Depthwise Separable Convolutional Networks Through the Eyes of Multi-scale Distributional Dynamics	Computer Vision and Pattern Recognition (cs.CV)	Stone Yun, Alexander Wong
2104.11883	Channel Pruning in a White Box for Efficient Image Classification	Computer Vision and Pattern Recognition (cs.CV)	Yuxin Zhang, Mingbao Lin, Chia-Wen Lin, Jie Chen, Feiyue Huang, Yongjian Wu, Yonghong Tian, Rongrong Ji
2104.11928	Extract then Distill: Efficient and Effective Task-Agnostic BERT Distillation	Computation and Language (cs.CL)	Cheng Chen, Yichun Yin, Lifeng Shang, Zhi Wang, Xin Jiang, Xiao Chen, Qun Liu
2104.12046	Quantization of Deep Neural Networks for Accurate EdgeComputing	Computer Vision and Pattern Recognition (cs.CV)	Wentao Chen, Hailong Qiu, Jian Zhuang, Chutong Zhang, Yu Hu, Qing Lu, Tianchen Wang, Yiyu Shi†, Meiping Huang, Xiaowe Xu
2104.12416	Communication-Efficient Federated Learning with Dual-Side Low-Rank Compression	Machine Learning (cs.LG)	Zhefeng Qiao, Xianghao Yu, Jun Zhang, Khaled B. Letaief
2104.12456	3D Scene Compression through Entropy Penalized Neural Representation Functions	Computer Vision and Pattern Recognition (cs.CV)	Thomas Bird, Johannes Ballé, Saurabh Singh, Philip A. Chou
2104.12528	Spatio-Temporal Pruning and Quantization for Low-latency Spiking Neural Networks	Machine Learning (cs.LG)	Sayeed Shafayet Chowdhury, Isha Garg, Kaushik Roy
2104.12592	Understanding and Accelerating EM Algorithm's Convergence by Fair Competition Principle and Rate-Verisimilitude Function	Machine Learning (cs.LG)	Chenguang Lu
2104.12770	Adaptive Encoding for Constrained Video Delivery in HEVC, VP9, AV1 and VVC Compression Standards and Adaptation to Video Content	Multimedia (cs.MM)	Gangadharan Esakki
2104.12861	Learning Interpretable End-to-End Vision-Based Motion Planning for Autonomous Driving with Optical Flow Distillation	Computer Vision and Pattern Recognition (cs.CV)	Hengli Wang, Peide Cai, Yuxiang Sun, Lujia Wang, Ming Liu
2104.12984	Accelerating Coordinate Descent via Active Set Selection for Device Activity Detection for Multi-Cell Massive Random Access	Signal Processing (eess.SP)	Ziyue Wang, Ya-Feng Liu, Zhilin Chen, Wei Yu
2104.13298	Self-distillation with Batch Knowledge Ensembling Improves ImageNet Classification	Computer Vision and Pattern Recognition (cs.CV)	Yixiao Ge, Ching Lam Choi, Xiao Zhang, Peipei Zhao, Feng Zhu, Rui Zhao, Hongsheng Li
2104.13343	Sifting out the features by pruning: Are convolutional networks the winning lottery ticket of fully connected ones?	Machine Learning (cs.LG)	Franco Pellegrini, Giulio Biroli
2104.13766	Boosting Co-teaching with Compression Regularization for Label Noise	Computer Vision and Pattern Recognition (cs.CV)	Yingyi Chen, Xi Shen, Shell Xu Hu, Johan A.K. Suykens
2104.13818	NUQSGD: Provably Communication-efficient Data-parallel SGD via Nonuniform Quantization	Machine Learning (cs.LG)	Ali Ramezani-Kebrya, Fartash Faghri, Ilya Markov, Vitalii Aksenov, Dan Alistarh, Daniel M. Roy
2104.13921	Zero-Shot Detection via Vision and Language Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Xiuye Gu, Tsung-Yi Lin, Weicheng Kuo, Yin Cui
2104.14117	Hessian Aware Quantization of Spiking Neural Networks	Neural and Evolutionary Computing (cs.NE)	Hin Wai Lui, Emre Neftci
2104.14203	Rethinking Ensemble-Distillation for Semantic Segmentation Based Unsupervised Domain Adaptation	Computer Vision and Pattern Recognition (cs.CV)	Chen-Hao Chao, Bo-Wun Cheng, Chun-Yi Lee
2104.14346	Bridging the gap between streaming and non-streaming ASR systems bydistilling ensembles of CTC and RNN-T models	Computation and Language (cs.CL)	Thibault Doutre, Wei Han, Chung-Cheng Chiu, Ruoming Pang, Olivier Siohan, Liangliang Cao
2104.14616	Learning in Feedforward Neural Networks Accelerated by Transfer Entropy	Machine Learning (cs.LG)	Adrian Moldovan, Angel Caţaron, Răzvan Andonie
2104.14696	Spirit Distillation: A Model Compression Method with Multi-domain Knowledge Transfer	Computer Vision and Pattern Recognition (cs.CV)	Zhiyuan Wu, Yu Jiang, Minghao Zhao, Chupeng Cui, Zongmin Yang, Xinhui Xue, Hong Qi
2104.14753	Studying the Consistency and Composability of Lottery Ticket Pruning Masks	Computer Vision and Pattern Recognition (cs.CV)	Rajiv Movva, Jonathan Frankle, Michael Carbin
2104.15023	Post-training deep neural network pruning via layer-wise calibration	Computer Vision and Pattern Recognition (cs.CV)	Ivan Lazarevich, Alexander Kozlov, Nikita Malinin
2104.15082	Semantic Relation Preserving Knowledge Distillation for Image-to-Image Translation	Computer Vision and Pattern Recognition (cs.CV)	Zeqi Li, Ruowei Jiang, Parham Aarabi
2105.00039	GPU Acceleration of 3D Agent-Based Biological Simulations	Distributed, Parallel, and Cluster Computing (cs.DC)	Ahmad Hesam, Lukas Breitwieser, Fons Rademakers, Zaid Al-Ars
2105.00104	Distilling EEG Representations via Capsules for Affective Computing	Machine Learning (cs.LG)	Guangyi Zhang, Ali Etemad
2105.00562	Personalized Federated Learning by Structured and Unstructured Pruning under Data Heterogeneity	Machine Learning (cs.LG)	Saeed Vahidian, Mahdi Morafah, Bill Lin
2105.00812	Layer Reduction: Accelerating Conformer-Based Self-Supervised Model via Layer Consistency	Computation and Language (cs.CL)	Jinchuan Tian, Rongzhi Gu, Helin Wang, Yuexian Zou
2105.01064	Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems	Information Retrieval (cs.IR)	Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal
2105.01237	COMISR: Compression-Informed Video Super-Resolution	Computer Vision and Pattern Recognition (cs.CV)	Yinxiao Li, Pengchong Jin, Feng Yang, Ce Liu, Ming-Hsuan Yang, Peyman Milanfar
2105.01353	One Model for All Quantization: A Quantized Network Supporting Hot-Swap Bit-Width Adjustment	Computer Vision and Pattern Recognition (cs.CV)	Qigong Sun, Xiufang Li, Yan Ren, Zhongjian Huang, Xu Liu, Licheng Jiao, Fang Liu
2105.01868	Q-Rater: Non-Convex Optimization for Post-Training Uniform Quantization	Machine Learning (cs.LG)	Byeongwook Kim, Dongsoo Lee, Yeonju Ro, Yongkweon Jeon, Se Jung Kwon, Baeseong Park, Daehwan Oh
2105.01875	Modulating Regularization Frequency for Efficient Compression-Aware Model Training	Machine Learning (cs.LG)	Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Jeongin Yun, Baeseong Park, Yongkweon Jeon
2105.02019	ScissionLite: Accelerating Distributed Deep Neural Networks Using Transfer Layer	Distributed, Parallel, and Cluster Computing (cs.DC)	Hyunho Ahn, Munkyu Lee, Cheol-Ho Hong, Blesson Varghese
2105.02936	Exact Acceleration of K-Means++ and K-Means$\|$	Machine Learning (cs.LG)	Edward Raff
2105.03120	Neural 3D Scene Compression via Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Berivan Isik
2105.03193	Network Pruning That Matters: A Case Study on Retraining Variants	Machine Learning (cs.LG)	Duong H. Le, Binh-Son Hua
2105.03308	Geometric convergence of elliptical slice sampling	Machine Learning (stat.ML)	Viacheslav Natarovskii, Daniel Rudolf, Björn Sprungk
2105.03343	Adapting by Pruning: A Case Study on BERT	Machine Learning (cs.LG)	Yang Gao, Nicolo Colombo, Wei Wang
2105.03365	Accelerating Entrepreneurial Decision-Making Through Hybrid Intelligence	Artificial Intelligence (cs.AI)	Dominik Dellermann
2105.03544	Test-Time Adaptation Toward Personalized Speech Enhancement: Zero-Shot Learning with Knowledge Distillation	Audio and Speech Processing (eess.AS)	Sunwoo Kim, Minje Kim
2105.03600	Incremental Training and Group Convolution Pruning for Runtime DNN Performance Scaling on Heterogeneous Embedded Platforms	Computer Vision and Pattern Recognition (cs.CV)	Lei Xun, Long Tran-Thanh, Bashir M Al-Hashimi, Geoff V. Merrett
2105.03736	PIM-DRAM: Accelerating Machine Learning Workloads using Processing in Commodity DRAM	Machine Learning (cs.LG)	Sourjya Roy, Mustafa Ali, Anand Raghunathan
2105.03918	Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics	Machine Learning (cs.LG)	Avik Pal, Yingbo Ma, Viral Shah, Christopher Rackauckas
2105.03933	Joint Learning of Deep Retrieval Model and Product Quantization based Embedding Index	Information Retrieval (cs.IR)	Han Zhang, Hongwei Shen, Yiming Qiu, Yunjiang Jiang, Songlin Wang, Sulong Xu, Yun Xiao, Bo Long, Wen-Yun Yang
2105.04181	KDExplainer: A Task-oriented Attention Model for Explaining Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Mengqi Xue, Jie Song, Xinchao Wang, Ying Chen, Xingen Wang, Mingli Song
2105.04218	Exploiting Elasticity in Tensor Ranks for Compressing Neural Networks	Machine Learning (cs.LG)	Jie Ran, Rui Lin, Hayden K.H. So, Graziano Chesi, Ngai Wong
2105.04246	In-Hindsight Quantization Range Estimation for Quantized Training	Machine Learning (cs.LG)	Marios Fournarakis, Markus Nagel
2105.04528	Accelerating Large Scale Real-Time GNN Inference using Channel Pruning	Machine Learning (cs.LG)	Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, Viktor Prasanna
2105.04550	Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth	Machine Learning (cs.LG)	Keyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi
2105.04916	Pruning of Deep Spiking Neural Networks through Gradient Rewiring	Neural and Evolutionary Computing (cs.NE)	Yanqi Chen, Zhaofei Yu, Wei Fang, Tiejun Huang, Yonghong Tian
2105.04937	Accelerating the SpMV kernel on standard CPUs by exploiting the partially diagonal structures	Distributed, Parallel, and Cluster Computing (cs.DC)	Takeshi Fukaya, Koki Ishida, Akie Miura, Takeshi Iwashita, Hiroshi Nakashima
2105.05071	Accelerating Amoebots via Reconfigurable Circuits	Distributed, Parallel, and Cluster Computing (cs.DC)	Michael Feldmann, Andreas Padalkin, Christian Scheideler, Shlomi Dolev
2105.05080	ANDREAS: Artificial intelligence traiNing scheDuler foR accElerAted resource clusterS	Distributed, Parallel, and Cluster Computing (cs.DC)	Federica Filippini, Danilo Ardagna, Marco Lattuada, Edoardo Amaldi, Michele Ciavotta, Maciek Riedl, Katarzyna Materka, Paweł Skrzypek, Fabrizio Magugliani, Marco Cicala
2105.05175	Mitigating Smart Meter Asynchrony Error Via Multi-Objective Low Rank Matrix Recovery	Signal Processing (eess.SP)	Yuxuan Yuan, Kaveh Dehghanpour, Zhaoyu Wang
2105.05521	SauvolaNet: Learning Adaptive Sauvola Network for Degraded Document Binarization	Computer Vision and Pattern Recognition (cs.CV)	Deng Li, Yue Wu, Yicong Zhou
2105.05708	Deep and Shallow Covariance Feature Quantization for 3D Facial Expression Recognition	Computer Vision and Pattern Recognition (cs.CV)	Walid Hariri, Nadir Farah, Dinesh Kumar Vishwakarma
2105.05912	MATE-KD: Masked Adversarial TExt, a Companion to Knowledge Distillation	Computation and Language (cs.CL)	Ahmad Rashid, Vasileios Lioutas, Mehdi Rezagholizadeh
2105.05916	Dynamical Isometry: The Missing Ingredient for Neural Network Pruning	Machine Learning (cs.LG)	Huan Wang, Can Qin, Yue Bai, Yun Fu
2105.06002	Lightweight compression of neural network feature tensors for collaborative intelligence	Machine Learning (cs.LG)	Robert A. Cohen, Hyomin Choi, Ivan V. Bajić
2105.06052	Model Pruning Based on Quantified Similarity of Feature Maps	Computer Vision and Pattern Recognition (cs.CV)	Zidu Wang, Xuexin Liu, Long Huang, Yunqing Chen, Yufei Zhang, Zhikang Lin, Rui Wang
2105.06125	Deep Unsupervised Hashing by Distilled Smooth Guidance	Computer Vision and Pattern Recognition (cs.CV)	Xiao Luo, Zeyu Ma, Daqing Wu, Huasong Zhong, Chong Chen, Jinwen Ma, Minghua Deng
2105.06143	Boosting Light-Weight Depth Estimation Via Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Junjie Hu, Chenyou Fan, Hualie Jiang, Xiyue Guo, Xiangyong Lu, Tin Lun Lam
2105.06250	3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low BitwidthQuantization, and Ultra-Low Latency Acceleration	Machine Learning (cs.LG)	Yao Chen, Cole Hawkins, Kaiqi Zhang, Zheng Zhang, Cong Hao
2105.06423	BWCP: Probabilistic Learning-to-Prune Channels for ConvNets via Batch Whitening	Machine Learning (cs.LG)	Wenqi Shao, Hang Yu, Zhaoyang Zhang, Hang Xu, Zhenguo Li, Ping Luo
2105.06514	Distilling BERT for low complexity network training	Computation and Language (cs.CL)	Bansidhar Mangalwedhekar
2105.06987	Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets	Machine Learning (cs.LG)	Max Ryabinin, Andrey Malinin, Mark Gales
2105.07102	Lightweight Compression of Intermediate Neural Network Features for Collaborative Intelligence	Machine Learning (cs.LG)	Robert A. Cohen, Hyomin Choi, Ivan V. Bajić
2105.07331	Is In-Domain Data Really Needed? A Pilot Study on Cross-Domain Calibration for Network Quantization	Machine Learning (cs.LG)	Haichao Yu, Linjie Yang, Humphrey Shi
2105.07351	Model-Based Offline Planning with Trajectory Pruning	Artificial Intelligence (cs.AI)	Xianyuan Zhan, Xiangyu Zhu, Haoran Xu
2105.07372	An accelerated expectation-maximization for multi-reference alignment	Signal Processing (eess.SP)	Noam Janco, Tamir Bendory
2105.07381	Undistillable: Making A Nasty Teacher That CANNOT teach students	Machine Learning (cs.LG)	Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, Zhangyang Wang
2105.07519	Graph-Free Knowledge Distillation for Graph Neural Networks	Machine Learning (cs.LG)	Xiang Deng, Zhongfei Zhang
2105.08252	Weakly Supervised Dense Video Captioning via Jointly Usage of Knowledge Distillation and Cross-modal Matching	Computer Vision and Pattern Recognition (cs.CV)	Bofeng Wu, Guocheng Niu, Jun Yu, Xinyan Xiao, Jian Zhang, Hua Wu
2105.08369	Inplace knowledge distillation with teacher assistant for improved training of flexible deep neural networks	Signal Processing (eess.SP)	Alexey Ozerov, Ngoc Duong
2105.08584	Contrastive Model Inversion for Data-Free Knowledge Distillation	Artificial Intelligence (cs.AI)	Gongfan Fang, Jie Song, Xinchao Wang, Chengchao Shen, Xingen Wang, Mingli Song
2105.08919	Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation	Machine Learning (cs.LG)	Taehyeon Kim, Jaehoon Oh, NakYil Kim, Sangwook Cho, Se-Young Yun
2105.08990	Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning	Machine Learning (cs.LG)	Maximilian Schenke, Oliver Wallscheid
2105.09080	Accelerating Gossip SGD with Periodic Global Averaging	Machine Learning (cs.LG)	Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
2105.09899	DeepAVO: Efficient Pose Refining with Feature Distilling for Deep Visual Odometry	Computer Vision and Pattern Recognition (cs.CV)	Ran Zhu, Mingkun Yang, Wang Liu, Rujun Song, Bo Yan, Zhuoling Xiao
2105.10056	Data-Free Knowledge Distillation for Heterogeneous Federated Learning	Machine Learning (cs.LG)	Zhuangdi Zhu, Junyuan Hong, Jiayu Zhou
2105.10059	Model Compression	Machine Learning (cs.LG)	Arhum Ishtiaq, Sara Mahmood, Maheen Anees, Neha Mumtaz
2105.10065	A Probabilistic Approach to Neural Network Pruning	Machine Learning (cs.LG)	Xin Qian, Diego Klabjan
2105.10288	Extremely Lightweight Quantization Robust Real-Time Single-Image Super Resolution for Mobile Devices	Computer Vision and Pattern Recognition (cs.CV)	Mustafa Ayazoglu
2105.10436	Compressing Deep CNNs using Basis Representation and Spectral Fine-tuning	Computer Vision and Pattern Recognition (cs.CV)	Muhammad Tayyab, Fahad Ahmad Khan, Abhijit Mahalanobis
2105.10633	Revisiting Knowledge Distillation for Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Amin Banitalebi-Dehkordi
2105.10832	Spectral Pruning for Recurrent Neural Networks	Machine Learning (stat.ML)	Takashi Furuya, Kazuma Suetake, Koichi Taniguchi, Hiroyuki Kusumoto, Ryuji Saiin, Tomohiro Daimon
2105.11010	Post-Training Sparsity-Aware Quantization	Machine Learning (cs.LG)	Gil Shomron, Freddy Gabbay, Samer Kurzum, Uri Weiser
2105.11025	Compressing Heavy-Tailed Weight Matrices for Non-Vacuous Generalization Bounds	Machine Learning (cs.LG)	John Y. Shin
2105.11228	Towards Compact CNNs via Collaborative Compression	Computer Vision and Pattern Recognition (cs.CV)	Yuchao Li, Shaohui Lin, Jianzhuang Liu, Qixiang Ye, Mengdi Wang, Fei Chao, Fan Yang, Jincheng Ma, Qi Tian, Rongrong Ji
2105.11354	View Distillation with Unlabeled Data for Extracting Adverse Drug Effects from User-Generated Data	Computation and Language (cs.CL)	Payam Karisani, Jinho D. Choi, Li Xiong
2105.11502	On the Genotype Compression and Expansion for Evolutionary Algorithms in the Continuous Domain	Neural and Evolutionary Computing (cs.NE)	Lucija Planinic, Marko Djurasevic, Luca Mariot, Domagoj Jakobovic, Stjepan Picek, Carlos Coello Coello
2105.11618	TR-BERT: Dynamic Token Reduction for Accelerating BERT Inference	Computation and Language (cs.CL)	Deming Ye, Yankai Lin, Yufei Huang, Maosong Sun
2105.11681	Deep Neural Networks and End-to-End Learning for Audio Compression	Machine Learning (cs.LG)	Daniela N. Rim, Inseon Jang, Heeyoul Choi
2105.11683	Towards Compact Single Image Super-Resolution via Contrastive Self-distillation	Computer Vision and Pattern Recognition (cs.CV)	Yanbo Wang, Shaohui Lin, Yanyun Qu, Haiyan Wu, Zhizhong Zhang, Yuan Xie, Angela Yao
2105.11730	Exploring Autoencoder-based Error-bounded Compression for Scientific Data	Machine Learning (cs.LG)	Jinyang Liu, Sheng Di, Kai Zhao, Sian Jin, Dingwen Tao, Xin Liang, Zizhong Chen, Franck Cappello
2105.12002	Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization	Machine Learning (cs.LG)	Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen
2105.12151	AutoReCon: Neural Architecture Search-based Reconstruction for Data-free Compression	Computer Vision and Pattern Recognition (cs.CV)	Baozhou Zhu, Peter Hofstee, Johan Peltenburg, Jinho Lee, Zaid Alars
2105.12900	How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation?	Computation and Language (cs.CL)	Weijia Xu, Shuming Ma, Dongdong Zhang, Marine Carpuat
2105.12912	CuSZ+: Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs	Distributed, Parallel, and Cluster Computing (cs.DC)	Jiannan Tian, Sheng Di, Xiaodong Yu, Cody Rivera, Kai Zhao, Sian Jin, Yunhe Feng, Xin Liang, Dingwen Tao, Franck Cappello
2105.12967	Selective Knowledge Distillation for Neural Machine Translation	Computation and Language (cs.CL)	Fusheng Wang, Jianhao Yan, Fandong Meng, Jie Zhou
2105.12971	Joint-DetNAS: Upgrade Your Detector with NAS, Pruning and Dynamic Distillation	Computer Vision and Pattern Recognition (cs.CV)	Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang
2105.13093	Towards Understanding Knowledge Distillation	Machine Learning (cs.LG)	Mary Phuong, Christoph H. Lampert
2105.13271	OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression	Machine Learning (cs.LG)	Nicola Bastianello, Andrea Simonetto, Emiliano Dall'Anese
2105.13331	Quantization and Deployment of Deep Neural Networks on Microcontrollers	Machine Learning (cs.LG)	Pierre-Emmanuel Novac (1), Ghouthi Boukli Hacene (2 and 3), Alain Pegatoquet (1), Benoît Miramond (1), Vincent Gripon (2) ((1) Université Côte d'Azur, CNRS, LEAT, Sophia Antipolis, France, (2) IMT Atlantique, Brest, France, (3) MILA, Montreal, Canada)
2105.13617	FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learning	Computer Vision and Pattern Recognition (cs.CV)	Minha Kim, Shahroz Tariq, Simon S. Woo
2105.13649	Pruning and Slicing Neural Networks using Formal Verification	Machine Learning (cs.LG)	Ori Lahav, Guy Katz
2105.13878	Accelerating BERT Inference for Sequence Labeling via Early-Exit	Computation and Language (cs.CL)	Xiaonan Li, Yunfan Shao, Tianxiang Sun, Hang Yan, Xipeng Qiu, Xuanjing Huang
2105.14044	Fair Representations by Compression	Machine Learning (cs.LG)	Xavier Gitiaux, Huzefa Rangwala
2105.14070	Accelerating Neural ODEs Using Model Order Reduction	Machine Learning (cs.LG)	Mikko Lehtimäki, Lassi Paunonen, Marja-Leena Linne
2105.14280	Hashing-Accelerated Graph Neural Networks for Link Prediction	Machine Learning (cs.LG)	Wei Wu, Bin Li, Chuan Luo, Wolfgang Nejdl
2105.14301	Rapid Feature Evolution Accelerates Learning in Neural Networks	Machine Learning (stat.ML)	Haozhe Shan, Blake Bordelon
2105.14416	Communication efficient privacy-preserving distributed optimization using adaptive differential quantization	Distributed, Parallel, and Cluster Computing (cs.DC)	Qiongxiu Li, Richard Heusdens, Mads Græsbøll Christensen
2105.14444	NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search	Computation and Language (cs.CL)	Jin Xu, Xu Tan, Renqian Luo, Kaitao Song, Jian Li, Tao Qin, Tie-Yan Liu
2105.14636	MLPruning: A Multilevel Structured Pruning Framework for Transformer-based Models	Computation and Language (cs.CL)	Zhewei Yao, Linjian Ma, Sheng Shen, Kurt Keutzer, Michael W. Mahoney
2105.14797	RED : Looking for Redundancies for Data-Free Structured Compression of Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly
2105.14839	Greedy Layer Pruning: Decreasing Inference Time of Transformer Models	Computation and Language (cs.CL)	David Peer, Sebastian Stabinger, Stefan Engl, Antonio Rodriguez-Sanchez
2105.14975	Privileged Graph Distillation for Cold Start Recommendation	Information Retrieval (cs.IR)	Shuai Wang, Kun Zhang, Le Wu, Haiping Ma, Richang Hong, Meng Wang
2105.15191	Unifying Distillation with Personalization in Federated Learning	Machine Learning (cs.LG)	Siddharth Divi, Habiba Farrukh, Berkay Celik
2106.00058	PUDLE: Implicit Acceleration of Dictionary Learning by Backpropagation	Machine Learning (cs.LG)	Bahareh Tolooshams, Demba Ba
2106.00127	Integer-Only Neural Network Quantization Scheme Based on Shift-Batch-Normalization	Machine Learning (cs.LG)	Qingyu Guo, Yuan Wang, Xiaoxin Cui
2106.00241	Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition	Computation and Language (cs.CL)	Shining Liang, Ming Gong, Jian Pei, Linjun Shou, Wanli Zuo, Xianglin Zuo, Daxin Jiang
2106.00368	Natural Statistics of Network Activations and Implications for Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Michael Rotman, Lior Wolf
2106.00526	A Compression-Compilation Framework for On-mobile Real-time BERT Applications	Machine Learning (cs.LG)	Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang
2106.00606	Dynamic-Deep: ECG Task-Aware Compression	Signal Processing (eess.SP)	Eli Brosh, Elad Wasserstein, Anat Bremler-Barr
2106.00612	Weak target detection with multi-bit quantization in colocated MIMO radar	Signal Processing (eess.SP)	Hang Xiao, Shixing Yang, Wei Yi
2106.00828	Refining the bounding volumes for lossless compression of voxelized point clouds geometry	Computer Vision and Pattern Recognition (cs.CV)	Emre Can Kaya, Sebastian Schwarz, Ioan Tabus
2106.00995	Energy-Efficient Model Compression and Splitting for Collaborative Inference Over Time-Varying Channels	Machine Learning (cs.LG)	Mounssif Krouka, Anis Elgabli, Chaouki Ben Issaid, Mehdi Bennis
2106.01023	One Teacher is Enough? Pre-trained Language Model Distillation from Multiple Teachers	Computation and Language (cs.CL)	Chuhan Wu, Fangzhao Wu, Yongfeng Huang
2106.01128	Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs	Machine Learning (cs.LG)	Meyer Scetbon, Gabriel Peyré, Marco Cuturi
2106.01134	Smooth Q-learning: Accelerate Convergence of Q-learning Using Similarity	Artificial Intelligence (cs.AI)	Wei Liao, Xiaohui Wei, Jizhou Lai
2106.01273	Chunk Content is not Enough: Chunk-Context Aware Resemblance Detection for Deduplication Delta Compression	Distributed, Parallel, and Cluster Computing (cs.DC)	Xuming Ye, Xiaoye Xue, Wenlong Tian, Zhiyong Xu, Weijun Xiao, Ruixuan Li
2106.01335	On the Distribution, Sparsity, and Inference-time Quantization of Attention Values in Transformers	Computation and Language (cs.CL)	Tianchu Ji, Shraddhan Jain, Michael Ferdman, Peter Milder, H. Andrew Schwartz, Niranjan Balasubramanian
2106.01504	DeepCompress: Efficient Point Cloud Geometry Compression	Computer Vision and Pattern Recognition (cs.CV)	Ryan Killea, Yun Li, Saeed Bastani, Paul McLachlan
2106.01625	Generate, Prune, Select: A Pipeline for Counterspeech Generation against Online Hate Speech	Computation and Language (cs.CL)	Wanzheng Zhu, Suma Bhat
2106.02205	Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators	Machine Learning (cs.LG)	Peiyu Liu, Ze-Feng Gao, Wayne Xin Zhao, Z.Y. Xie, Zhong-Yi Lu, Ji-Rong Wen
2106.02241	ERNIE-Tiny : A Progressive Distillation Framework for Pretrained Transformer Compression	Computation and Language (cs.CL)	Weiyue Su, Xuyi Chen, Shikun Feng, Jiaxiang Liu, Weixin Liu, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang
2106.02295	Differentiable Dynamic Quantization with Mixed Precision and Adaptive Resolution	Machine Learning (cs.LG)	Zhang Zhaoyang, Shao Wenqi, Gu Jinwei, Wang Xiaogang, Luo Ping
2106.02299	MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution	Computer Vision and Pattern Recognition (cs.CV)	Liying Lu, Wenbo Li, Xin Tao, Jiangbo Lu, Jiaya Jia
2106.02435	You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature Gradient	Computation and Language (cs.CL)	Shaokun Zhang, Xiawu Zheng, Chenyi Yang, Yuchao Li, Yan Wang, Fei Chao, Mengdi Wang, Shen Li, Jun Yang, Rongrong Ji
2106.02614	Sigma-Delta and Distributed Noise-Shaping Quantization Methods for Random Fourier Features	Machine Learning (cs.LG)	Jinjie Zhang, Alexander Cloninger, Rayan Saab
2106.02654	Churn Reduction via Distillation	Machine Learning (cs.LG)	Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh
2106.02697	Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees	Machine Learning (cs.LG)	Philip A. Etter, Kai Zhong, Hsiang-Fu Yu, Lexing Ying, Inderjit Dhillon
2106.02770	Accelerating Stochastic Simulation with Interactive Neural Processes	Machine Learning (cs.LG)	Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
2106.02834	MergeDistill: Merging Pre-trained Language Models using Distillation	Computation and Language (cs.CL)	Simran Khanuja, Melvin Johnson, Partha Talukdar
2106.02870	Bidirectional Distillation for Top-K Recommender System	Information Retrieval (cs.IR)	Wonbin Kweon, SeongKu Kang, Hwanjo Yu
2106.03097	Preservation of the Global Knowledge by Not-True Self Knowledge Distillation in Federated Learning	Machine Learning (cs.LG)	Gihun Lee, Yongjin Shin, Minchan Jeong, Se-Young Yun
2106.03310	Zero-Shot Knowledge Distillation from a Decision-Based Black-Box Model	Machine Learning (cs.LG)	Zi Wang
2106.03441	Attention Temperature Matters in Abstractive Summarization Distillation	Computation and Language (cs.CL)	Shengqiang Zhang, Xingxing Zhang, Hangbo Bao, Furu Wei
2106.03524	Smoothness-Aware Quantization Techniques	Machine Learning (cs.LG)	Bokun Wang, Mher Safaryan, Peter Richtárik
2106.03613	RoSearch: Search for Robust Student Architectures When Distilling Pre-trained Language Models	Computation and Language (cs.CL)	Xin Guo, Jianlei Yang, Haoyi Zhou, Xucheng Ye, Jianxin Li
2106.03795	Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks	Machine Learning (stat.ML)	Melih Barsbey, Milad Sefidgaran, Murat A. Erdogdu, Gaël Richard, Umut Şimşekli
2106.04195	Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation	Computer Vision and Pattern Recognition (cs.CV)	Pengpeng Liu, Michael R. Lyu, Irwin King, Jia Xu
2106.04208	Grapevine Winter Pruning Automation: On Potential Pruning Points Detection through 2D Plant Modeling using Grapevine Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Miguel Fernandes, Antonello Scaldaferri, Giuseppe Fiameni, Tao Teng, Matteo Gatti, Stefano Poni, Claudio Semini, Darwin Caldwell, Fei Chen
2106.04411	Fair Feature Distillation for Visual Recognition	Computer Vision and Pattern Recognition (cs.CV)	Sangwon Jung, Donggyu Lee, Taeeon Park, Taesup Moon
2106.04563	XtremeDistilTransformers: Task Transfer for Task-agnostic Distillation	Computation and Language (cs.CL)	Subhabrata Mukherjee, Ahmed Hassan Awadallah, Jianfeng Gao
2106.04570	Meta Learning for Knowledge Distillation	Machine Learning (cs.LG)	Wangchunshu Zhou, Canwen Xu, Julian McAuley
2106.04784	Accelerating Neural Architecture Search via Proxy Data	Machine Learning (cs.LG)	Byunggook Na, Jisoo Mok, Hyeokjun Choe, Sungroh Yoon
2106.04928	Reliable Adversarial Distillation with Unreliable Teachers	Machine Learning (cs.LG)	Jianing Zhu, Jiangchao Yao, Bo Han, Jingfeng Zhang, Tongliang Liu, Gang Niu, Jingren Zhou, Jianliang Xu, Hongxia Yang
2106.05209	Distilling Image Classifiers in Object Detectors	Computer Vision and Pattern Recognition (cs.CV)	Shuxuan Guo, Jose M. Alvarez, Mathieu Salzmann
2106.05237	Knowledge distillation: A good teacher is patient and consistent	Computer Vision and Pattern Recognition (cs.CV)	Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov
2106.05691	Marginal Utility Diminishes: Exploring the Minimum Knowledge for BERT Knowledge Distillation	Computation and Language (cs.CL)	Yuanxin Liu, Fandong Meng, Zheng Lin, Weiping Wang, Jie Zhou
2106.05933	PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition	Computation and Language (cs.CL)	Cheng-I Jeff Lai, Yang Zhang, Alexander H. Liu, Shiyu Chang, Yi-Lun Liao, Yung-Sung Chuang, Kaizhi Qian, Sameer Khurana, David Cox, James Glass
2106.05945	Does Knowledge Distillation Really Work?	Machine Learning (cs.LG)	Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A. Alemi, Andrew Gordon Wilson
2106.06091	DECORE: Deep Compression with Reinforcement Learning	Artificial Intelligence (cs.AI)	Manoj Alwani, Vashisht Madhavan, Yang Wang
2106.06168	Generate, Annotate, and Learn: Generative Models Advance Self-Training and Knowledge Distillation	Machine Learning (cs.LG)	Xuanli He, Islam Nassar, Jamie Kiros, Gholamreza Haffari, Mohammad Norouzi
2106.06921	Adaptive Dynamic Pruning for Non-IID Federated Learning	Machine Learning (cs.LG)	Sixing Yu, Phuong Nguyen, Ali Anwar, Ali Jannesari
2106.06955	Towards Understanding Iterative Magnitude Pruning: Why Lottery Tickets Win	Machine Learning (cs.LG)	Jaron Maene, Mingxiao Li, Marie-Francine Moens
2106.06963	Exploring and Distilling Posterior and Prior Knowledge for Radiology Report Generation	Computer Vision and Pattern Recognition (cs.CV)	Fenglin Liu, Xian Wu, Shen Ge, Wei Fan, Yuexian Zou
2106.07172	Energy-efficient Knowledge Distillation for Spiking Neural Networks	Neural and Evolutionary Computing (cs.NE)	Dongjin Lee, Seongsik Park, Jongwan Kim, Wuhyeong Doh, Sungroh Yoon
2106.07611	Neuroevolution-Enhanced Multi-Objective Optimization for Mixed-Precision Quantization	Neural and Evolutionary Computing (cs.NE)	Santiago Miret, Vui Seng Chua, Mattias Marder, Mariano Phielipp, Nilesh Jain, Somdeb Majumdar
2106.07734	CoDERT: Distilling Encoder Representations with Co-learning for Transducer-based Speech Recognition	Computation and Language (cs.CL)	Rupak Vignesh Swaminathan, Brian King, Grant P. Strimel, Jasha Droppo, Athanasios Mouchtaris
2106.07807	Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data	Computer Vision and Pattern Recognition (cs.CV)	Ashraful Islam, Chun-Fu Chen, Rameswar Panda, Leonid Karlinsky, Rogerio Feris, Richard J. Radke
2106.07849	Simon Says: Evaluating and Mitigating Bias in Pruned Neural Networks with Knowledge Distillation	Machine Learning (cs.LG)	Cody Blakeney, Nathaniel Huish, Yan Yan, Ziliang Zong
2106.07898	Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral	Machine Learning (stat.ML)	Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaid Harchaoui
2106.07989	Compression Implies Generalization	Machine Learning (cs.LG)	Allan Grønlund, Mikael Høgsgaard, Lior Kamma, Kasper Green Larsen
2106.07994	Multi-channel Opus compression for far-field automatic speech recognition with a fixed bitrate budget	Audio and Speech Processing (eess.AS)	Lukas Drude, Jahn Heymann, Andreas Schwarz, Jean-Marc Valin
2106.08181	Direction is what you need: Improving Word Embedding Compression in Large Language Models	Computation and Language (cs.CL)	Klaudia Bałazy, Mohammadreza Banaei, Rémi Lebret, Jacek Tabor, Karl Aberer
2106.08295	A White Paper on Neural Network Quantization	Machine Learning (cs.LG)	Markus Nagel, Marios Fournarakis, Rana Ali Amjad, Yelysei Bondarenko, Mart van Baalen, Tijmen Blankevoort
2106.08301	Efficient Micro-Structured Weight Unification and Pruning for Neural Network Compression	Machine Learning (cs.LG)	Sheng Lin, Wei Jiang, Wei Wang, Kaidi Xu, Yanzhi Wang, Shan Liu, Songnan Li
2106.08512	Revisit Visual Representation in Analytics Taxonomy: A Compression Perspective	Computer Vision and Pattern Recognition (cs.CV)	Yueyu Hu, Wenhan Yang, Haofeng Huang, Jiaying Liu
2106.08541	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages	Machine Learning (cs.LG)	Yi Luo, Aiguo Chen, Ke Yan, Ling Tian
2106.08700	Topology Distillation for Recommender System	Machine Learning (cs.LG)	SeongKu Kang, Junyoung Hwang, Wonbin Kweon, Hwanjo Yu
2106.08898	RefBERT: Compressing BERT by Referencing to Pre-computed Representations	Computation and Language (cs.CL)	Xinyi Wang, Haiqin Yang, Liang Zhao, Yang Mo, Jianping Shen
2106.09129	A Winning Hand: Compressing Deep Networks Can Improve Out-Of-Distribution Robustness	Machine Learning (cs.LG)	James Diffenderfer, Brian R. Bartoldson, Shreya Chaganti, Jize Zhang, Bhavya Kailkhura
2106.09166	Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI	Machine Learning (cs.LG)	Geng Yuan, Zhiheng Liao, Xiaolong Ma, Yuxuan Cai, Zhenglun Kong, Xuan Shen, Jingyan Fu, Zhengang Li, Chengming Zhang, Hongwu Peng, Ning Liu, Ao Ren, Jinhui Wang, Yanzhi Wang
2106.09216	Layer Pruning on Demand with Intermediate CTC	Audio and Speech Processing (eess.AS)	Jaesong Lee, Jingu Kang, Shinji Watanabe
2106.09269	Pruning Randomly Initialized Neural Networks with Iterative Randomization	Machine Learning (cs.LG)	Daiki Chijiwa, Shin'ya Yamaguchi, Yasutoshi Ida, Kenji Umakoshi, Tomohiro Inoue
2106.09517	Dynamic Knowledge Distillation with A Single Stream Structure for RGB-D Salient Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Guangyu Ren, Tania Stathaki
2106.09564	Knowledge distillation from multi-modal to mono-modal segmentation networks	Computer Vision and Pattern Recognition (cs.CV)	Minhao Hu, Matthis Maillard, Ya Zhang, Tommaso Ciceri, Giammarco La Barbera, Isabelle Bloch, Pietro Gori
2106.09703	MoDist: Motion Distillation for Self-supervised Video Representation Learning	Computer Vision and Pattern Recognition (cs.CV)	Fanyi Xiao, Joseph Tighe, Davide Modolo
2106.09821	Generalized Learning Vector Quantization for Classification in Randomized Neural Networks and Hyperdimensional Computing	Machine Learning (cs.LG)	Cameron Diao, Denis Kleyko, Jan M. Rabaey, Bruno A. Olshausen
2106.09831	On Effects of Compression with Hyperdimensional Computing in Distributed Randomized Neural Networks	Machine Learning (cs.LG)	Antonello Rosato, Massimo Panella, Evgeny Osipov, Denis Kleyko
2106.09857	Effective Model Sparsification by Scheduled Grow-and-Prune Methods	Computer Vision and Pattern Recognition (cs.CV)	Xiaolong Ma, Minghai Qin, Fei Sun, Zejiang Hou, Kun Yuan, Yi Xu, Yanzhi Wang, Yen-Kuang Chen, Rong Jin, Yuan Xie
2106.09886	Quantized Neural Networks via {-1, +1} Encoding Decomposition and Acceleration	Computer Vision and Pattern Recognition (cs.CV)	Qigong Sun, Xiufang Li, Fanhua Shang, Hongying Liu, Kang Yang, Licheng Jiao, Zhouchen Lin
2106.10132	VQMIVC: Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversion	Audio and Speech Processing (eess.AS)	Disong Wang, Liqun Deng, Yu Ting Yeung, Xiao Chen, Xunying Liu, Helen Meng
2106.10404	Sparse Training via Boosting Pruning Plasticity with Neuroregeneration	Machine Learning (cs.LG)	Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
2106.10494	Teacher's pet: understanding and mitigating biases in distillation	Machine Learning (cs.LG)	Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar
2106.10566	Accelerated Policy Evaluation: Learning Adversarial Environments with Adaptive Importance Sampling	Machine Learning (cs.LG)	Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao
2106.10591	Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density Estimation	Machine Learning (stat.ML)	Magda Amiridi, Nikos Kargas, Nicholas D. Sidiropoulos
2106.10796	CD-SGD: Distributed Stochastic Gradient Descent with Compression and Delay Compensation	Machine Learning (cs.LG)	Enda Yu, Dezun Dong, Yemao Xu, Shuo Ouyang, Xiangke Liao
2106.10800	Lossy Compression for Lossless Prediction	Machine Learning (cs.LG)	Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J. Maddison
2106.10820	Compressing Deep ODE-Nets using Basis Function Expansions	Machine Learning (cs.LG)	Alejandro Queiruga, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney
2106.10885	Knowledge Distillation via Instance-level Sequence Learning	Computer Vision and Pattern Recognition (cs.CV)	Haoran Zhao, Xin Sun, Junyu Dong, Zihe Dong, Qiong Li
2106.11099	Distilling effective supervision for robust medical image segmentation with noisy labels	Computer Vision and Pattern Recognition (cs.CV)	Jialin Shi, Ji Wu
2106.11197	Iterative Network Pruning with Uncertainty Regularization for Lifelong Sentiment Classification	Computation and Language (cs.CL)	Binzong Geng, Min Yang, Fajie Yuan, Shupeng Wang, Xiang Ao, Ruifeng Xu
2106.11304	Simple Distillation Baselines for Improving Small Self-supervised Models	Computer Vision and Pattern Recognition (cs.CV)	Jindong Gu, Wei Liu, Yonglong Tian
2106.11524	On Minimizing Symbol Error Rate Over Fading Channels with Low-Resolution Quantization	Signal Processing (eess.SP)	Neil Irwin Bernardo, Jingge Zhu, Jamie Evans
2106.11542	Differentiable Architecture Search Without Training Nor Labels: A Pruning Perspective	Machine Learning (cs.LG)	Miao Zhang, Steven Su, Shirui Pan, Xiaojun Chang, Wei Huang, Gholamreza Haffari
2106.12169	APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores	Distributed, Parallel, and Cluster Computing (cs.DC)	Boyuan Feng, Yuke Wang, Tong Geng, Ang Li, Yufei Ding
2106.12378	Co-advise: Cross Inductive Bias Distillation	Computer Vision and Pattern Recognition (cs.CV)	Sucheng Ren, Zhengqi Gao, Tianyu Hua, Zihui Xue, Yonglong Tian, Shengfeng He, Hang Zhao
2106.12699	Distilling the Knowledge from Conditional Normalizing Flows	Machine Learning (cs.LG)	Dmitry Baranchuk, Vladimir Aliev, Artem Babenko
2106.12718	Sparse Flows: Pruning Continuous-depth Models	Machine Learning (cs.LG)	Lucas Liebenwein, Ramin Hasani, Alexander Amini, Daniela Rus
2106.12736	Frequency Domain Convolutional Neural Network: Accelerated CNN for Large Diabetic Retinopathy Image Classification	Computer Vision and Pattern Recognition (cs.CV)	Ee Fey Goh, ZhiYuan Chen, Wei Xiang Lim
2106.13035	Quantization Aware Training, ERNIE and Kurtosis Regularizer: a short empirical study	Machine Learning (stat.ML)	Andrea Zanetti
2106.13266	DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Giorgos Kordopatis-Zilos, Christos Tzelepis, Symeon Papadopoulos, Ioannis Kompatsiaris, Ioannis Patras
2106.13474	Adapt-and-Distill: Developing Small, Fast and Effective Pretrained Language Models for Domains	Computation and Language (cs.CL)	Yunzhi Yao, Shaohan Huang, Wenhui Wang, Li Dong, Furu Wei
2106.13574	Multiview Video Compression Using Advanced HEVC Screen Content Coding	Multimedia (cs.MM)	Jarosław Samelak, Marek Domański
2106.13652	A mechanistic-based data-driven approach to accelerate structural topology optimization through finite element convolutional neural network (FE-CNN)	Machine Learning (cs.LG)	Tianle Yue, Hang Yang, Zongliang Du, Chang Liu, Khalil I. Elkhodary, Shan Tang, Xu Guo
2106.13686	Cross-Modal Knowledge Distillation Method for Automatic Cued Speech Recognition	Multimedia (cs.MM)	Jianrong Wang, Ziyue Tang, Xuewei Li, Mei Yu, Qiang Fang, Li Liu
2106.13972	Exploring Spatial Indexing for Accelerated Feature Retrieval in HPC	Distributed, Parallel, and Cluster Computing (cs.DC)	Margaret Lawson, William Gropp, Jay Lofstead
2106.14089	Accelerating Recurrent Neural Networks for Gravitational Wave Experiments	Machine Learning (cs.LG)	Zhiqiang Que, Erwei Wang, Umar Marikar, Eric Moreno, Jennifer Ngadiuba, Hamza Javed, Bartłomiej Borzyszkowski, Thea Aarrestad, Vladimir Loncar, Sioni Summers, Maurizio Pierini, Peter Y Cheung, Wayne Luk
2106.14126	AdaptCL: Efficient Collaborative Learning with Dynamic and Adaptive Pruning	Machine Learning (cs.LG)	Guangmeng Zhou, Ke Xu, Qi Li, Yang Liu, Yi Zhao
2106.14156	Post-Training Quantization for Vision Transformer	Computer Vision and Pattern Recognition (cs.CV)	Zhenhua Liu, Yunhe Wang, Kai Han, Siwei Ma, Wen Gao
2106.14190	Mitigating severe over-parameterization in deep convolutional neural networks through forced feature abstraction and compression with an entropy-based heuristic	Computer Vision and Pattern Recognition (cs.CV)	Nidhi Gowdra, Roopak Sinha, Stephen MacDonell, Wei Qi Yan
2106.14681	PQK: Model Compression via Pruning, Quantization, and Knowledge Distillation	Machine Learning (cs.LG)	Jangho Kim, Simyung Chang, Nojun Kwak
2106.14943	Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search	Computer Vision and Pattern Recognition (cs.CV)	Pu Zhao, Wei Niu, Geng Yuan, Yuxuan Cai, Bin Ren, Yanzhi Wang, Xue Lin
2106.15315	Boggart: Accelerating Retrospective Video Analytics via Model-Agnostic Ingest Processing	Computer Vision and Pattern Recognition (cs.CV)	Neil Agarwal, Ravi Netravali
2106.16002	Distributed Nash Equilibrium Seeking under Quantization Communication	Distributed, Parallel, and Cluster Computing (cs.DC)	Ziqin Chen, Ji Ma, Shu Liang, Li Li
2106.16126	Recognizing Facial Expressions in the Wild using Multi-Architectural Representations based Ensemble Learning with Distillation	Computer Vision and Pattern Recognition (cs.CV)	Rauf Momin, Ali Shan Momin, Khalid Rasheed, Muhammad Saqib
2107.00051	Global Knowledge Distillation in Federated Learning	Machine Learning (cs.LG)	Wanning Pan, Lichao Sun
2107.00067	Fair Visual Recognition in Limited Data Regime using Self-Supervision and Self-Distillation	Computer Vision and Pattern Recognition (cs.CV)	Pratik Mazumder, Pravendra Singh, Vinay P. Namboodiri
2107.00181	Revisiting Knowledge Distillation: An Inheritance and Exploration Framework	Machine Learning (cs.LG)	Zhen Huang, Xu Shen, Jun Xing, Tongliang Liu, Xinmei Tian, Houqiang Li, Bing Deng, Jianqiang Huang, Xian-Sheng Hua
2107.00327	Orthonormal Product Quantization Network for Scalable Face Image Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Ming Zhang, Xuefei Zhe, Hong Yan
2107.00328	End-to-end Compression Towards Machine Vision: Network Architecture Design and Optimization	Computer Vision and Pattern Recognition (cs.CV)	Shurun Wang, Zhao Wang, Shiqi Wang, Yan Ye
2107.00364	Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks with Bottlenecks	Machine Learning (cs.LG)	Etai Littwin, Omid Saremi, Shuangfei Zhai, Vimal Thilak, Hanlin Goh, Joshua M. Susskind, Greg Yang
2107.00411	Knowledge Distillation for Quality Estimation	Computation and Language (cs.CL)	Amit Gajbhiye, Marina Fomicheva, Fernando Alva-Manchego, Frédéric Blain, Abiola Obamuyide, Nikolaos Aletras, Lucia Specia
2107.00595	Fast Margin Maximization via Dual Acceleration	Machine Learning (cs.LG)	Ziwei Ji, Nathan Srebro, Matus Telgarsky
2107.00703	Distilling Reinforcement Learning Tricks for Video Games	Machine Learning (cs.LG)	Anssi Kanervisto, Christian Scheller, Yanick Schraner, Ville Hautamäki
2107.00910	Learned Token Pruning for Transformers	Computation and Language (cs.CL)	Sehoon Kim, Sheng Shen, David Thorsley, Amir Gholami, Joseph Hassoun, Kurt Keutzer
2107.01081	Neural Network Layer Algebra: A Framework to Measure Capacity and Compression in Deep Learning	Machine Learning (cs.LG)	Alberto Badias, Ashis Banerjee
2107.01173	Momentum Accelerates the Convergence of Stochastic AUPRC Maximization	Machine Learning (cs.LG)	Guanghui Wang, Ming Yang, Lijun Zhang, Tianbao Yang
2107.01192	CHISEL: Compression-Aware High-Accuracy Embedded Indoor Localization with Deep Learning	Machine Learning (cs.LG)	Liping Wang, Saideep Tiku, Sudeep Pasricha
2107.01378	Efficient Vision Transformers via Fine-Grained Manifold Distillation	Computer Vision and Pattern Recognition (cs.CV)	Ding Jia, Kai Han, Yunhe Wang, Yehui Tang, Jianyuan Guo, Chao Zhang, Dacheng Tao
2107.01412	Isotonic Data Augmentation for Knowledge Distillation	Machine Learning (cs.LG)	Wanyun Cui, Sen Yan
2107.01787	Multi-View Correlation Distillation for Incremental Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Dongbao Yang, Yu Zhou, Weiping Wang
2107.01808	Why is Pruning at Initialization Immune to Reinitializing and Shuffling?	Machine Learning (cs.LG)	Sahib Singh, Rosanne Liu
2107.01832	Provable Convergence of Nesterov Accelerated Method for Over-Parameterized Neural Networks	Machine Learning (cs.LG)	Xin Liu, Zhisong Pan
2107.01952	Partition and Code: learning how to compress graphs	Machine Learning (cs.LG)	Giorgos Bouritsas, Andreas Loukas, Nikolaos Karalias, Michael M. Bronstein
2107.02027	Packing: Towards 2x NLP BERT Acceleration	Computation and Language (cs.CL)	Matej Kosec, Sheng Fu, Mario Michael Krell
2107.02086	One-Cycle Pruning: Pruning ConvNets Under a Tight Training Budget	Computer Vision and Pattern Recognition (cs.CV)	Nathan Hubens, Matei Mancas, Bernard Gosselin, Marius Preda, Titus Zaharia
2107.02306	Connectivity Matters: Neural Network Pruning Through the Lens of Effective Sparsity	Machine Learning (cs.LG)	Artem Vysogorets, Julia Kempe
2107.02408	CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation	Computer Vision and Pattern Recognition (cs.CV)	Minha Kim, Shahroz Tariq, Simon S. Woo
2107.02500	Generalizing Nucleus Recognition Model in Multi-source Images via Pruning	Computer Vision and Pattern Recognition (cs.CV)	Jiatong Cai, Chenglu Zhu, Can Cui, Honglin Li, Tong Wu, Shichuan Zhang, Lin Yang
2107.02520	Deep Learning Methods for Joint Optimization of Beamforming and Fronthaul Quantization in Cloud Radio Access Networks	Signal Processing (eess.SP)	Daesung Yu, Hoon Lee, Seok-Hwan Park, Seung-Eun Hong
2107.02629	Embracing the Dark Knowledge: Domain Generalization Using Regularized Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yufei Wang, Haoliang Li, Lap-pui Chau, Alex C. Kot
2107.02655	Automatic size and pose homogenization with spatial transformer network to improve and accelerate pediatric segmentation	Computer Vision and Pattern Recognition (cs.CV)	Giammarco La Barbera, Pietro Gori, Haithem Boussaid, Bruno Belucci, Alessandro Delmonte, Jeanne Goulin, Sabine Sarnacki, Laurence Rouet, Isabelle Bloch
2107.02681	VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer	Computation and Language (cs.CL)	Zineng Tang, Jaemin Cho, Hao Tan, Mohit Bansal
2107.03225	Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification	Computer Vision and Pattern Recognition (cs.CV)	Xiaohan Xing, Yuenan Hou, Hang Li, Yixuan Yuan, Hongsheng Li, Max Q.-H. Meng
2107.03356	Efficient Matrix-Free Approximations of Second-Order Information, with Applications to Pruning and Optimization	Machine Learning (cs.LG)	Elias Frantar, Eldar Kurtic, Dan Alistarh
2107.03358	Novel Visual Category Discovery with Dual Ranking Statistics and Mutual Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Bingchen Zhao, Kai Han
2107.03375	Differentiable Architecture Pruning for Transfer Learning	Machine Learning (cs.LG)	Nicolo Colombo, Yang Gao
2107.03909	Weight Reparametrization for Budget-Aware Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Robin Dupont, Hichem Sahbi, Guillaume Michel
2107.04074	Accelerating Spherical k-Means	Machine Learning (cs.LG)	Erich Schubert, Andreas Lang, Gloria Feher
2107.04191	Structured Model Pruning of Convolutional Networks on Tensor Processing Units	Machine Learning (cs.LG)	Kongtao Chen, Ken Franko, Ruoxin Sang
2107.04380	Model compression as constrained optimization, with application to neural nets. Part V: combining compressions	Machine Learning (cs.LG)	Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev
2107.04386	Joint Matrix Decomposition for Deep Convolutional Neural Networks Compression	Computer Vision and Pattern Recognition (cs.CV)	Shaowu Chen, Jiahao Zhou, Weize Sun, Lei Huang
2107.04746	Consensual Collaborative Training And Knowledge Distillation Based Facial Expression Recognition Under Noisy Annotations	Computer Vision and Pattern Recognition (cs.CV)	Darshan Gera, S. Balasubramanian
2107.05033	Blending Pruning Criteria for Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Wei He, Zhongzhan Huang, Mingfu Liang, Senwei Liang, Haizhao Yang
2107.05298	HEMP: High-order Entropy Minimization for neural network comPression	Machine Learning (cs.LG)	Enzo Tartaglione, Stéphane Lathuilière, Attilio Fiandrotti, Marco Cagnazzo, Marco Grangetto
2107.05328	Structured Directional Pruning via Perturbation Orthogonal Projection	Machine Learning (cs.LG)	YinchuanLi, XiaofengLiu, YunfengShao, QingWang, YanhuiGeng
2107.05473	GPTPU: Accelerating Applications using Edge Tensor Processing Units	Distributed, Parallel, and Cluster Computing (cs.DC)	Kuan-Chieh Hsu, Hung-Wei Tseng
2107.05583	Few-shot Learning with Global Relatedness Decoupled-Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yuan Zhou, Yanrong Guo, Shijie Hao, Richang Hong, Zhen junzha, Meng Wang
2107.05787	Data-Driven Low-Rank Neural Network Compression	Machine Learning (cs.LG)	Dimitris Papadimitriou, Swayambhoo Jain
2107.06492	RCLC: ROI-based joint conventional and learning video compression	Multimedia (cs.MM)	Trinh Man Hoang, Jinjia Zhou
2107.06533	Accelerating Distributed K-FAC with Smart Parallelism of Computing and Communication Tasks	Distributed, Parallel, and Cluster Computing (cs.DC)	Shaohuai Shi, Lin Zhang, Bo Li
2107.06960	Memory-Aware Fusing and Tiling of Neural Networks for Accelerated Edge Inference	Machine Learning (cs.LG)	Jackson Farley, Andreas Gerstlauer
2107.06993	Confidence Conditioned Knowledge Distillation	Machine Learning (cs.LG)	Sourav Mishra, Suresh Sundaram
2107.07173	Scene-adaptive Knowledge Distillation for Sequential Recommendation via Differentiable Architecture Search	Information Retrieval (cs.IR)	Lei Chen, Fajie Yuan, Jiaxi Yang, Min Yang, Chengming Li
2107.07331	Modeling Accurate Human Activity Recognition for Embedded Devices Using Multi-level Distillation	Machine Learning (cs.LG)	Runze Chen, Haiyong Luo, Fang Zhao, Xuechun Meng, Zhiqing Xie, Yida Zhu
2107.07467	Only Train Once: A One-Shot Neural Network Training And Pruning Framework	Machine Learning (cs.LG)	Tianyi Chen, Bo Ji, Tianyu Ding, Biyi Fang, Guanyi Wang, Zhihui Zhu, Luming Liang, Yixin Shi, Sheng Yi, Xiao Tu
2107.07651	Align before Fuse: Vision and Language Representation Learning with Momentum Distillation	Computer Vision and Pattern Recognition (cs.CV)	Junnan Li, Ramprasaath R. Selvaraju, Akhilesh Deepak Gotmare, Shafiq Joty, Caiming Xiong, Steven Hoi
2107.07737	EGC2: Enhanced Graph Classification with Easy Graph Compression	Machine Learning (cs.LG)	Jinyin Chen, Dunjie Zhang, Zhaoyan Ming, Mingwei Jia, Yi Liu
2107.08173	Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and Masking	Computation and Language (cs.CL)	Binzong Geng, Fajie Yuan, Qiancheng Xu, Ying Shen, Ruifeng Xu, Min Yang
2107.08382	A High-Performance Adaptive Quantization Approach for Edge CNN Applications	Computer Vision and Pattern Recognition (cs.CV)	Hsu-Hsun Chin, Ren-Song Tsay, Hsin-I Wu
2107.08591	Double Similarity Distillation for Semantic Image Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Yingchao Feng, Xian Sun, Wenhui Diao, Jihao Li, Xin Gao
2107.08815	Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data	Machine Learning (cs.LG)	Jiandong Mu, Mengdi Wang, Feiwen Zhu, Jun Yang, Wei Lin, Wei Zhang
2107.08849	Exploring the efficacy of neural networks for trajectory compression and the inverse problem	Machine Learning (cs.LG)	Theodoros Ntakouris
2107.08939	Detection of Double Compression in MPEG-4 Videos Using Refined Features-based CNN	Multimedia (cs.MM)	Seung-Hun Nam, Wonhyuk Ahn, Myung-Joon Kwon, In-Jae Yu
2107.09095	A New Clustering-Based Technique for the Acceleration of Deep Convolutional Networks	Machine Learning (cs.LG)	Erion-Vasilis Pikoulis, Christos Mavrokefalidis, Aris S. Lalos
2107.09101	Accelerating deep neural networks for efficient scene understanding in automotive cyber-physical systems	Computer Vision and Pattern Recognition (cs.CV)	Stavros Nousias, Erion-Vasilis Pikoulis, Christos Mavrokefalidis, Aris S. Lalos
2107.09145	Adaptive wavelet distillation from neural networks through interpretations	Machine Learning (stat.ML)	Wooseok Ha, Chandan Singh, Francois Lanusse, Srigokul Upadhyayula, Bin Yu
2107.09305	Follow Your Path: a Progressive Method for Knowledge Distillation	Machine Learning (cs.LG)	Wenxian Shi, Yuxuan Song, Hao Zhou, Bohan Li, Lei Li
2107.09461	CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression	Machine Learning (cs.LG)	Zhize Li, Peter Richtárik
2107.09574	Accelerating Edge Intelligence via Integrated Sensing and Communication	Signal Processing (eess.SP)	Tong Zhang, Shuai Wang, Guoliang Li, Fan Liu, Guangxu Zhu, Rui Wang
2107.09625	Learning ULMFiT and Self-Distillation with Calibration for Medical Dialogue System	Computation and Language (cs.CL)	Shuang Ao, Xeno Acharya
2107.09716	Regularized Classification-Aware Quantization	Machine Learning (cs.LG)	Daniel Severo, Elad Domanovitz, Ashish Khisti
2107.10254	Neural Fixed-Point Acceleration for Convex Optimization	Machine Learning (cs.LG)	Shobha Venkataraman, Brandon Amos
2107.10404	DeepScale: An Online Frame Size Adaptation Approach to Accelerate Visual Multi-object Tracking	Computer Vision and Pattern Recognition (cs.CV)	Keivan Nalaie, Rong Zheng
2107.10847	Accelerating Quadratic Optimization with Reinforcement Learning	Machine Learning (cs.LG)	Jeffrey Ichnowski, Paras Jain, Bartolomeo Stellato, Goran Banjac, Michael Luo, Francesco Borrelli, Joseph E. Gonzalez, Ion Stoica, Ken Goldberg
2107.10998	Pruning Ternary Quantization	Computer Vision and Pattern Recognition (cs.CV)	Dan Liu, Xi Chen, Jie Fu, Xue Liu
2107.11442	Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition	Machine Learning (cs.LG)	Lucas Liebenwein, Alaa Maalouf, Oren Gal, Dan Feldman, Daniela Rus
2107.11789	ROD: Reception-aware Online Distillation for Sparse Graphs	Machine Learning (cs.LG)	Wentao Zhang, Yuezihan Jiang, Yang Li, Zeang Sheng, Yu Shen, Xupeng Miao, Liang Wang, Zhi Yang, Bin Cui
2107.12081	Towards the Unseen: Iterative Text Recognition by Distilling from Errors	Computer Vision and Pattern Recognition (cs.CV)	Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Aneeshan Sain, Yi-Zhe Song
2107.12087	Text is Text, No Matter What: Unifying Text Recognition using Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Ayan Kumar Bhunia, Aneeshan Sain, Pinaki Nath Chowdhury, Yi-Zhe Song
2107.12250	Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models	Machine Learning (cs.LG)	Zhiliang Wu, Yinchong Yang, Peter A. Fasching, Volker Tresp
2107.12422	Towards Efficient Tensor Decomposition-Based DNN Model Compression with Optimization Framework	Computer Vision and Pattern Recognition (cs.CV)	Miao Yin, Yang Sui, Siyu Liao, Bo Yuan
2107.12428	Improving Word Recognition in Speech Transcriptions by Decision-level Fusion of Stemming and Two-way Phoneme Pruning	Computation and Language (cs.CL)	Sunakshi Mehra, Seba Susan
2107.12445	Towards Low-Latency Energy-Efficient Deep SNNs via Attention-Guided Compression	Neural and Evolutionary Computing (cs.NE)	Souvik Kundu, Gourav Datta, Massoud Pedram, Peter A. Beerel
2107.12452	Accelerated Gradient Descent Learning over Multiple Access Fading Channels	Machine Learning (cs.LG)	Raz Paul, Yuval Friedman, Kobi Cohen
2107.12673	COPS: Controlled Pruning Before Training Starts	Machine Learning (cs.LG)	Paul Wimmer, Jens Mehnert, Alexandru Condurache
2107.13034	Dataset Distillation with Infinitely Wide Convolutional Networks	Machine Learning (cs.LG)	Timothy Nguyen, Roman Novak, Lechao Xiao, Jaehoon Lee
2107.13715	Hierarchical Self-supervised Augmented Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Chuanguang Yang, Zhulin An, Linhang Cai, Yongjun Xu
2107.13797	HAFLO: GPU-Based Acceleration for Federated Logistic Regression	Machine Learning (cs.LG)	Xiaodian Cheng, Wanhang Lu, Xinyang Huang, Shuihai Hu, Kai Chen
2107.13892	QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning	Machine Learning (cs.LG)	Kaan Ozkara, Navjot Singh, Deepesh Data, Suhas Diggavi
2107.14415	Learnable Compression Network with Transformer for Approximate Nearest Neighbor Search	Information Retrieval (cs.IR)	Haokui Zhang, Wenze Hu, Xiaoyu Wang, Buzhou Tang
2107.14444	Manipulating Identical Filter Redundancy for Efficient Pruning on Deep and Complicated CNN	Computer Vision and Pattern Recognition (cs.CV)	Xiaohan Ding, Tianxiang Hao, Jungong Han, Yuchen Guo, Guiguang Ding
2107.14525	The Minimum Edit Arborescence Problem and Its Use in Compressing Graph Collections [Extended Version]	Computer Vision and Pattern Recognition (cs.CV)	Lucas Gnecco, Nicolas Boria, Sébastien Bougleux, Florian Yger, David B. Blumenthal
2107.14575	DQ-SGD: Dynamic Quantization in SGD for Communication-Efficient Distributed Learning	Machine Learning (cs.LG)	Guangfeng Yan, Shao-Lun Huang, Tian Lan, Linqi Song
2107.14762	On the Efficacy of Small Self-Supervised Contrastive Models without Distillation Signals	Machine Learning (cs.LG)	Haizhou Shi, Youcai Zhang, Siliang Tang, Wenjie Zhu, Yaqian Li, Yandong Guo, Yueting Zhuang
2108.00065	Pruning Neural Networks with Interpolative Decompositions	Machine Learning (cs.LG)	Jerry Chee, Megan Renz, Anil Damle, Chris De Sa
2108.00139	Pose-Guided Feature Learning with Knowledge Distillation for Occluded Person Re-Identification	Computer Vision and Pattern Recognition (cs.CV)	Kecheng Zheng, Cuiling Lan, Wenjun Zeng, Jiawei Liu, Zhizheng Zhang, Zheng-Jun Zha
2108.00187	Unsupervised Cross-Modal Distillation for Thermal Infrared Tracking	Computer Vision and Pattern Recognition (cs.CV)	Jingxian Sun, Lichao Zhang, Yufei Zha, Abel Gonzalez-Garcia, Peng Zhang, Wei Huang, Yanning Zhang
2108.00257	BoA-PTA, A Bayesian Optimization Accelerated Error-Free SPICE Solver	Machine Learning (cs.LG)	Wei W. Xing, Xiang Jin, Yi Liu, Dan Niu, Weishen Zhao, Zhou Jin
2108.00529	BigGraphVis: Leveraging Streaming Algorithms and GPU Acceleration for Visualizing Big Graphs	Distributed, Parallel, and Cluster Computing (cs.DC)	Ehsan Moradi, Debajyoti Mondal
2108.00587	Semi-Supervising Learning, Transfer Learning, and Knowledge Distillation with SimCLR	Computer Vision and Pattern Recognition (cs.CV)	Khoi Nguyen, Yen Nguyen, Bao Le
2108.00644	Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance	Information Retrieval (cs.IR)	Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma
2108.00708	Group Fisher Pruning for Practical Network Compression	Computer Vision and Pattern Recognition (cs.CV)	Liyang Liu, Shilong Zhang, Zhanghui Kuang, Aojun Zhou, Jing-Hao Xue, Xinjiang Wang, Yimin Chen, Wenming Yang, Qingmin Liao, Wayne Zhang
2108.01192	Multi-objective Recurrent Neural Networks Optimization for the Edge -- a Quantization-based Approach	Machine Learning (cs.LG)	Nesma M. Rezk, Tomas Nordström, Dimitrios Stathis, Zain Ul-Abdin, Eren Erdal Aksoy, Ahmed Hemani
2108.01358	Accelerating the Convergence of Human-in-the-Loop Reinforcement Learning with Counterfactual Explanations	Artificial Intelligence (cs.AI)	Jakob Karalus, Felix Lindner
2108.02092	Online Knowledge Distillation for Efficient Pose Estimation	Computer Vision and Pattern Recognition (cs.CV)	Zheng Li, Jingwen Ye, Mingli Song, Ying Huang, Zhigeng Pan
2108.02191	Random Offset Block Embedding Array (ROBE) for CriteoTB Benchmark MLPerf DLRM Model : 1000$\times$ Compression and 2.7$\times$ Faster Inference	Information Retrieval (cs.IR)	Aditya Desai, Li Chou, Anshumali Shrivastava
2108.02479	HyperJump: Accelerating HyperBand via Risk Modelling	Machine Learning (cs.LG)	Pedro Mendes, Maria Casimiro, Paolo Romano
2108.02569	Data Streaming and Traffic Gathering in Mesh-based NoC for Deep Neural Network Acceleration	Machine Learning (cs.LG)	Binayak Tiwari, Mei Yang, Xiaohang Wang, Yingtao Jiang
2108.02598	Knowledge Distillation from BERT Transformer to Speech Transformer for Intent Classification	Computation and Language (cs.CL)	Yidi Jiang, Bidisha Sharma, Maulik Madhavi, Haizhou Li
2108.02696	A Low Rank Promoting Prior for Unsupervised Contrastive Learning	Computer Vision and Pattern Recognition (cs.CV)	Yu Wang, Jingyang Lin, Qi Cai, Yingwei Pan, Ting Yao, Hongyang Chao, Tao Mei
2108.02720	Generalizable Mixed-Precision Quantization via Attribution Rank Preservation	Computer Vision and Pattern Recognition (cs.CV)	Ziwei Wang, Han Xiao, Jiwen Lu, Jie Zhou
2108.02893	Basis Scaling and Double Pruning for Efficient Transfer Learning	Computer Vision and Pattern Recognition (cs.CV)	Ken C. L. Wong, Satyananda Kashyap, Mehdi Moradi
2108.03084	Transferring Knowledge Distillation for Multilingual Social Event Detection	Machine Learning (cs.LG)	Jiaqian Ren, Hao Peng, Lei Jiang, Jia Wu, Yongxin Tong, Lihong Wang, Xu Bai, Bo Wang, Qiang Yang
2108.03322	Distilling Transformers for Neural Cross-Domain Search	Information Retrieval (cs.IR)	Colin B. Clement, Chen Wu, Dawn Drain, Neel Sundaresan
2108.03470	A distillation based approach for the diagnosis of diseases	Computer Vision and Pattern Recognition (cs.CV)	Hmrishav Bandyopadhyay, Shuvayan Ghosh Dastidar, Bisakh Mondal, Biplab Banerjee, Nibaran Das
2108.03543	Spatio-Temporal Attention Mechanism and Knowledge Distillation for Lip Reading	Computer Vision and Pattern Recognition (cs.CV)	Shahd Elashmawy, Marian Ramsis, Hesham M. Eraqi, Farah Eldeshnawy, Hadeel Mabrouk, Omar Abugabal, Nourhan Sakr
2108.03619	Learning an Augmented RGB Representation with Cross-Modal Knowledge Distillation for Action Detection	Computer Vision and Pattern Recognition (cs.CV)	Rui Dai, Srijan Das, Francois Bremond
2108.03819	DistillPose: Lightweight Camera Localization Using Auxiliary Learning	Computer Vision and Pattern Recognition (cs.CV)	Yehya Abouelnaga, Mai Bui, Slobodan Ilic
2108.04448	Decentralized Composite Optimization with Compression	Machine Learning (cs.LG)	Yao Li, Xiaorui Liu, Jiliang Tang, Ming Yan, Kun Yuan
2108.04541	Accelerating Evolutionary Neural Architecture Search via Multi-Fidelity Evaluation	Artificial Intelligence (cs.AI)	Shangshang Yang, Ye Tian, Xiaoshu Xiang, Shichen Peng, Xingyi Zhang
2108.04657	Differentiable Subset Pruning of Transformer Heads	Computation and Language (cs.CL)	Jiaoda Li, Ryan Cotterell, Mrinmaya Sachan
2108.04890	On the Effect of Pruning on Adversarial Robustness	Computer Vision and Pattern Recognition (cs.CV)	Artur Jordao, Helio Pedrini
2108.05187	Discriminative Distillation to Reduce Class Confusion in Continual Learning	Computer Vision and Pattern Recognition (cs.CV)	Changhong Zhong, Zhiying Cui, Ruixuan Wang, Wei-Shi Zheng
2108.05507	Distilling Holistic Knowledge with Graph Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Sheng Zhou, Yucheng Wang, Defang Chen, Jiawei Chen, Xin Wang, Can Wang, Jiajun Bu
2108.05698	Preventing Catastrophic Forgetting and Distribution Mismatch in Knowledge Distillation via Synthetic Data	Machine Learning (cs.LG)	Kuluhan Binici, Nam Trung Pham, Tulika Mitra, Karianto Leman
2108.05872	HAC Explore: Accelerating Exploration with Hierarchical Reinforcement Learning	Artificial Intelligence (cs.AI)	Willie McClinton, Andrew Levy, George Konidaris
2108.06004	A Distributed SGD Algorithm with Global Sketching for Deep Learning Training Acceleration	Distributed, Parallel, and Cluster Computing (cs.DC)	LingFei Dai, Boyu Diao, Chao Li, Yongjun Xu
2108.06017	AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric Learning	Computer Vision and Pattern Recognition (cs.CV)	Hong Wang, Yuefan Deng, Shinjae Yoo, Haibin Ling, Yuewei Lin
2108.06227	SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Chenyu You, Yuan Zhou, Ruihan Zhao, Lawrence Staib, James S. Duncan
2108.06600	A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Qi Zhao, Binghao Liu, Shuchang Lyu, Xu Wang, Yifan Yang
2108.06626	A Survey on GAN Acceleration Using Memory Compression Technique	Machine Learning (cs.LG)	Dina Tantawy, Mohamed Zahran, Amr Wassal
2108.06629	LayerPipe: Accelerating Deep Neural Network Training by Intra-Layer and Inter-Layer Gradient Pipelining and Multiprocessor Scheduling	Distributed, Parallel, and Cluster Computing (cs.DC)	Nanda K. Unnikrishnan, Keshab K. Parhi
2108.06681	Multi-granularity for knowledge distillation	Computer Vision and Pattern Recognition (cs.CV)	Baitan Shao, Ying Chen
2108.06898	Neural-to-Tree Policy Distillation with Policy Improvement Criterion	Machine Learning (cs.LG)	Zhao-Hua Li, Yang Yu, Yingfeng Chen, Ke Chen, Zhipeng Hu, Changjie Fan
2108.06908	Online Multi-Granularity Distillation for GAN Compression	Computer Vision and Pattern Recognition (cs.CV)	Yuxi Ren, Jie Wu, Xuefeng Xiao, Jianchao Yang
2108.06983	Distance-aware Quantization	Computer Vision and Pattern Recognition (cs.CV)	Dohyung kim, Junghyup Lee, Bumsub Ham
2108.07466	Transferring Knowledge with Attention Distillation for Multi-Domain Image-to-Image Translation	Computer Vision and Pattern Recognition (cs.CV)	Runze Li, Tomaso Fontanini, Luca Donati, Andrea Prati, Bir Bhanu
2108.07482	G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation	Computer Vision and Pattern Recognition (cs.CV)	Lewei Yao, Renjie Pi, Hang Xu, Wei Zhang, Zhenguo Li, Tong Zhang
2108.07827	Compressing gradients by exploiting temporal correlation in momentum-SGD	Machine Learning (cs.LG)	Tharindu B. Adikari, Stark C. Draper
2108.07961	Verifying Low-dimensional Input Neural Networks via Input Quantization	Machine Learning (cs.LG)	Kai Jia, Martin Rinard
2108.08042	Joint Multiple Intent Detection and Slot Filling via Self-distillation	Computation and Language (cs.CL)	Lisong Chen, Peilin Zhou, Yuexian Zou
2108.08474	Trends in Neural Architecture Search: Towards the Acceleration of Search	Machine Learning (cs.LG)	Youngkee Kim, Won Joon Yun, Youn Kyu Lee, Soyi Jung, Joongheon Kim
2108.08532	An Information Theory-inspired Strategy for Automatic Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Xiawu Zheng, Yuexiao Ma, Teng Xi, Gang Zhang, Errui Ding, Yuchao Li, Jie Chen, Yonghong Tian, Rongrong Ji
2108.08560	Pruning in the Face of Adversaries	Machine Learning (cs.LG)	Florian Merkle, Maximilian Samsinger, Pascal Schöttle
2108.08903	SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep Neural Networks	Machine Learning (cs.LG)	Gokul Krishnan, Sumit K. Mandal, Manvitha Pannala, Chaitali Chakrabarti, Jae-sun Seo, Umit Y. Ogras, Yu Cao
2108.09134	Accelerating Federated Learning with a Global Biased Optimiser	Machine Learning (cs.LG)	Jed Mills, Jia Hu, Geyong Min, Rui Jin, Siwei Zheng, Jin Wang
2108.09183	Knowledge Distillation from Ensemble of Offsets for Head Pose Estimation	Computer Vision and Pattern Recognition (cs.CV)	Andrey Sheka, Victor Samun
2108.09484	CushLEPOR: Customised hLEPOR Metric Using LABSE Distilled Knowledge Model to Improve Agreement with Human Judgements	Computation and Language (cs.CL)	Lifeng Han, Irina Sorokina, Gleb Erofeev, Serge Gladkoff
2108.10078	Distilling Neuron Spike with High Temperature in Reinforcement Learning Agents	Neural and Evolutionary Computing (cs.NE)	Ling Zhang, Jian Cao, Yuan Zhang, Bohan Zhou, Shuo Feng
2108.10341	Query Embedding Pruning for Dense Retrieval	Information Retrieval (cs.IR)	Nicola Tonellotto, Craig Macdonald
2108.10394	Dynamic Network Quantization for Efficient Video Inference	Computer Vision and Pattern Recognition (cs.CV)	Ximeng Sun, Rameswar Panda, Chun-Fu Chen, Aude Oliva, Rogerio Feris, Kate Saenko
2108.10503	Small Object Detection Based on Modified FSSD and Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Qingcai Wang, Hao Zhang, Xianggong Hong, Qinqin Zhou
2108.10520	Improving Object Detection by Label Assignment Distillation	Computer Vision and Pattern Recognition (cs.CV)	Chuong H. Nguyen, Thuy C. Nguyen, Tuan N. Tang, Nam L.H. Phan
2108.10710	PocketNet: Extreme Lightweight Face Recognition Network using Neural Architecture Search and Multi-Step Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Fadi Boutros, Patrick Siebke, Marcel Klemt, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
2108.11798	Efficient training of lightweight neural networks using Online Self-Acquired Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Maria Tzelepi, Anastasios Tefas
2108.11877	A Deep Learning Loss Function based on Auditory Power Compression for Speech Enhancement	Audio and Speech Processing (eess.AS)	Tianrui Wang, Weibin Zhu
2108.11898	Supervised Compression for Resource-constrained Edge Computing Systems	Computer Vision and Pattern Recognition (cs.CV)	Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
2108.11932	H2OPUS-TLR: High Performance Tile Low Rank Symmetric Factorizations using Adaptive Randomized Approximation	Distributed, Parallel, and Cluster Computing (cs.DC)	Wajih Boukaram, Stefano Zampini, George Turkiyyah, David Keyes
2108.11939	Understanding and Accelerating Neural Architecture Search with Training-Free and Theory-Grounded Metrics	Machine Learning (cs.LG)	Wuyang Chen, Xinyu Gong, Yunchao Wei, Humphrey Shi, Zhicheng Yan, Yi Yang, Zhangyang Wang
2108.12074	4-bit Quantization of LSTM-based Speech Recognition Models	Computation and Language (cs.CL)	Andrea Fasoli, Chia-Yu Chen, Mauricio Serrano, Xiao Sun, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei Zhang, Zoltán Tüske, Kailash Gopalakrishnan
2108.12582	Distilling the Knowledge of Large-scale Generative Models into Retrieval Models for Efficient Open-domain Conversation	Computation and Language (cs.CL)	Beomsu Kim, Seokjun Seo, Seungju Han, Enkhbayar Erdenee, Buru Chang
2108.12594	Layer-wise Model Pruning based on Mutual Information	Computation and Language (cs.CL)	Chun Fan, Jiwei Li, Xiang Ao, Fei Wu, Yuxian Meng, Xiaofei Sun
2108.12604	Threshold: Pruning Tool for Densely Connected Convolutional Networks	Computer Vision and Pattern Recognition (cs.CV)	Rui-Yang Ju, Ting-Yu Lin, Jen-Shiun Chiang
2108.12659	DKM: Differentiable K-Means Clustering Layer for Neural Network Compression	Machine Learning (cs.LG)	Minsik Cho, Keivan A. Vahid, Saurabh Adya, Mohammad Rastegari
2108.12704	Compact representations of convolutional neural networks via weight pruning and quantization	Machine Learning (cs.LG)	Giosuè Cataldo Marinò, Alessandro Petrini, Dario Malchiodi, Marco Frasca
2108.12905	Lipschitz Continuity Guided Knowledge Distillation	Machine Learning (cs.LG)	Yuzhang Shang, Bin Duan, Ziliang Zong, Liqiang Nie, Yan Yan
2108.13323	FedKD: Communication Efficient Federated Learning via Knowledge Distillation	Machine Learning (cs.LG)	Chuhan Wu, Fangzhao Wu, Ruixuan Liu, Lingjuan Lyu, Yongfeng Huang, Xing Xie
2108.13342	DNNFusion: Accelerating Deep Neural Networks Execution with Advanced Operator Fusion	Machine Learning (cs.LG)	Wei Niu, Jiexiong Guan, Yanzhi Wang, Gagan Agrawal, Bin Ren
2108.13591	AIP: Adversarial Iterative Pruning Based on Knowledge Transfer for Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Jingfei Chang, Yang Lu, Ping Xue, Yiqun Xu, Zhen Wei
2108.13728	Pruning with Compensation: Efficient Channel Pruning for Deep Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Zhouyang Xie, Yan Fu, Shengzhao Tian, Junlin Zhou, Duanbing Chen
2108.13996	Quantization of Generative Adversarial Networks for Efficient Inference: a Methodological Study	Artificial Intelligence (cs.AI)	Pavel Andreev (1, 2, 3), Alexander Fritzler (1, 2, 4), Dmitry Vetrov (1, 3, 5) ((1) Higher School of Economics, (2) Skolkovo Institute of Science and Technology, (3) Samsung AI Center Moscow, (4) Yandex, (5) Samsung-HSE Laboratory)
2109.00212	Diverse Sample Generation: Pushing the Limit of Data-free Quantization	Computer Vision and Pattern Recognition (cs.CV)	Haotong Qin, Yifu Ding, Xiangguo Zhang, Aoyu Li, Jiakai Wang, Xianglong Liu, Jiwen Lu
2109.00485	Accelerating an Iterative Eigensolver for Nuclear Structure Configuration Interaction Calculations on GPUs using OpenACC	Distributed, Parallel, and Cluster Computing (cs.DC)	Pieter Maris, Chao Yang, Dossay Oryspayev, Brandon Cook
2109.00516	Multistage Pruning of CNN Based ECG Classifiers for Edge Devices	Machine Learning (cs.LG)	Xiaolin Li, Rajesh Panicker, Barry Cardiff, Deepu John
2109.00525	Catastrophic Interference in Reinforcement Learning: A Solution Based on Context Division and Knowledge Distillation	Machine Learning (cs.LG)	Tiantian Zhang, Xueqian Wang, Bin Liang, Bo Yuan
2109.00537	ASVspoof 2021: accelerating progress in spoofed and deepfake speech detection	Audio and Speech Processing (eess.AS)	Junichi Yamagishi, Xin Wang, Massimiliano Todisco, Md Sahidullah, Jose Patino, Andreas Nautsch, Xuechen Liu, Kong Aik Lee, Tomi Kinnunen, Nicholas Evans, Héctor Delgado
2109.00857	Optimal Path Planning of Autonomous Marine Vehicles in Stochastic Dynamic Ocean Flows using a GPU-Accelerated Algorithm	Artificial Intelligence (cs.AI)	Rohit Chowdhury, Deepak Subramani
2109.01305	Video Pose Distillation for Few-Shot, Fine-Grained Sports Action Recognition	Computer Vision and Pattern Recognition (cs.CV)	James Hong, Matthew Fisher, Michaël Gharbi, Kayvon Fatahalian
2109.01572	Using Topological Framework for the Design of Activation Function and Model Pruning in Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Yogesh Kochar, Sunil Kumar Vengalil, Neelam Sinha
2109.01731	Acceleration Method for Learning Fine-Layered Optical Neural Networks	Machine Learning (cs.LG)	Kazuo Aoyama, Hiroshi Sawada
2109.02100	Cluster-Promoting Quantization with Bit-Drop for Minimizing Network Quantization Loss	Machine Learning (cs.LG)	Jung Hyun Lee, Jihun Yun, Sung Ju Hwang, Eunho Yang
2109.02137	Efficient Action Recognition Using Confidence Distillation	Computer Vision and Pattern Recognition (cs.CV)	Shervin Manzuri Shalmani, Fei Chiang, Rong Zheng
2109.02220	GDP: Stabilized Neural Network Pruning via Gates with Differentiable Polarization	Computer Vision and Pattern Recognition (cs.CV)	Yi Guo, Huan Yuan, Jianchao Tan, Zhangyang Wang, Sen Yang, Ji Liu
2109.02244	Self-supervised Product Quantization for Deep Unsupervised Image Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Young Kyun Jang, Nam Ik Cho
2109.02426	Complementary Calibration: Boosting General Continual Learning with Collaborative Distillation and Self-Supervision	Computer Vision and Pattern Recognition (cs.CV)	Zhong Ji, Jin Li, Qiang Wang, Zhongfei Zhang
2109.03040	Reconfigurable co-processor architecture with limited numerical precision to accelerate deep convolutional neural networks	Machine Learning (cs.LG)	Sasindu Wijeratne, Sandaruwan Jayaweera, Mahesh Dananjaya, Ajith Pasqual
2109.03075	Knowledge Distillation Using Hierarchical Self-Supervision Augmented Distribution	Computer Vision and Pattern Recognition (cs.CV)	Chuanguang Yang, Zhulin An, Linhang Cai, Yongjun Xu
2109.03228	Beyond Preserved Accuracy: Evaluating Loyalty and Robustness of BERT Compression	Computation and Language (cs.CL)	Canwen Xu, Wangchunshu Zhou, Tao Ge, Ke Xu, Julian McAuley, Furu Wei
2109.03459	Dual Correction Strategy for Ranking Distillation in Top-N Recommender System	Information Retrieval (cs.IR)	Youngjune Lee, Kee-Eung Kim
2109.03513	Elastic Significant Bit Quantization and Acceleration for Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Cheng Gong, Ye Lu, Kunpeng Xie, Zongming Jin, Tao Li, Yanzhi Wang
2109.04075	Self Supervision to Distillation for Long-Tailed Visual Recognition	Computer Vision and Pattern Recognition (cs.CV)	Tianhao Li, Limin Wang, Gangshan Wu
2109.04186	Fine-grained Data Distribution Alignment for Post-Training Quantization	Computer Vision and Pattern Recognition (cs.CV)	Yunshan Zhong, Mingbao Lin, Mengzhao Chen, Ke Li, Yunhang Shen, Fei Chao, Yongjian Wu, Feiyue Huang, Rongrong Ji
2109.04197	A distillation-based approach integrating continual learning and federated learning for pervasive services	Artificial Intelligence (cs.AI)	Anastasiia Usmanova (INPG), François Portet (GETALP), Philippe Lalanda (M-PSI), German Vega (M-PSI)
2109.04236	ECQ$^{\text{x}}$: Explainability-Driven Quantization for Low-Bit and Sparse DNNs	Machine Learning (cs.LG)	Daniel Becking, Maximilian Dreyer, Wojciech Samek, Karsten Müller, Sebastian Lapuschkin
2109.04626	A Fast PC Algorithm with Reversed-order Pruning and A Parallelization Strategy	Machine Learning (cs.LG)	Kai Zhang, Chao Tian, Kun Zhang, Todd Johnson, Xiaoqian Jiang
2109.04653	Towards Developing a Multilingual and Code-Mixed Visual Question Answering System by Knowledge Distillation	Computation and Language (cs.CL)	Humair Raj Khan, Deepak Gupta, Asif Ekbal
2109.04660	Dynamic Collective Intelligence Learning: Finding Efficient Sparse Model via Refined Gradients for Pruned Weights	Machine Learning (cs.LG)	Jangho Kim, Jayeon Yoo, Yeji Song, KiYoon Yoo, Nojun Kwak
2109.04838	Block Pruning For Faster Transformers	Machine Learning (cs.LG)	François Lagunas, Ella Charlaix, Victor Sanh, Alexander M. Rush
2109.05075	On the Compression of Neural Networks Using $\ell_0$-Norm Regularization and Weight Pruning	Machine Learning (cs.LG)	Felipe Dennis de Resende Oliveira, Eduardo Luiz Ortiz Batista, Rui Seara
2109.05151	Accelerated Distributed Laplacian Solvers via Shortcuts	Distributed, Parallel, and Cluster Computing (cs.DC)	Ioannis Anagnostides, Themis Gouleakis, Christoph Lenzen
2109.05205	Contrastive Quantization with Code Memory for Unsupervised Image Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Jinpeng Wang, Ziyun Zeng, Bin Chen, Tao Dai, Shu-Tao Xia
2109.05206	Pyramid Hybrid Pooling Quantization for Efficient Fine-Grained Image Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Ziyun Zeng, Jinpeng Wang, Bin Chen, Tao Dai, Shu-Tao Xia
2109.05388	The Impact of Positional Encodings on Multilingual Compression	Computation and Language (cs.CL)	Vinit Ravishankar, Anders Søgaard
2109.05410	Accelerating GPU-Based Out-of-Core Stencil Computation with On-the-Fly Compression	Distributed, Parallel, and Cluster Computing (cs.DC)	Jingcheng Shen, Yifan Wu, Masao Okita, Fumihiko Ino
2109.05587	On the Efficiency of Subclass Knowledge Distillation in Classification Tasks	Machine Learning (cs.LG)	Ahmad Sajedi, Konstantinos N. Plataniotis
2109.05696	How to Select One Among All? An Extensive Empirical Study Towards the Robustness of Knowledge Distillation in Natural Language Understanding	Computation and Language (cs.CL)	Tianda Li, Ahmad Rashid, Aref Jafari, Pranav Sharma, Ali Ghodsi, Mehdi Rezagholizadeh
2109.05812	UniMS: A Unified Framework for Multimodal Summarization with Knowledge Distillation	Computation and Language (cs.CL)	Zhengkun Zhang, Xiaojun Meng, Yasheng Wang, Xin Jiang, Qun Liu, Zhenglu Yang
2109.06243	KroneckerBERT: Learning Kronecker Decomposition for Pre-trained Language Models via Knowledge Distillation	Computation and Language (cs.CL)	Marzieh S. Tahaei, Ella Charlaix, Vahid Partovi Nia, Ali Ghodsi, Mehdi Rezagholizadeh
2109.06379	Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation	Computation and Language (cs.CL)	Mingkai Deng, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu
2109.06397	AdaPruner: Adaptive Channel Pruning and Effective Weights Inheritance	Computer Vision and Pattern Recognition (cs.CV)	Xiangcheng Liu, Jian Cao, Hongyi Yao, Wenyu Sun, Yuan Zhang
2109.06458	Exploring the Connection between Knowledge Distillation and Logits Matching	Machine Learning (cs.LG)	Defang Chen, Can Wang, Yan Feng, Chun Chen
2109.06875	Multi-Scale Aligned Distillation for Low-Resolution Detection	Computer Vision and Pattern Recognition (cs.CV)	Lu Qi, Jason Kuen, Jiuxiang Gu, Zhe Lin, Yi Wang, Yukang Chen, Yanwei Li, Jiaya Jia
2109.06931	Measurement and Analysis of GPU-accelerated Applications with HPCToolkit	Distributed, Parallel, and Cluster Computing (cs.DC)	Keren Zhou, Laksono Adhianto, Jonathon Anderson, Aaron Cherian, Dejan Grubisic, Mark Krentel, Yumeng Liu, Xiaozhu Meng, John Mellor-Crummey
2109.07009	Will this Question be Answered? Question Filtering via Answer Model Distillation for Efficient Question Answering	Computation and Language (cs.CL)	Siddhant Garg, Alessandro Moschitti
2109.07222	EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation	Computation and Language (cs.CL)	Chenhe Dong, Guangrun Wang, Hang Xu, Jiefeng Peng, Xiaozhe Ren, Xiaodan Liang
2109.07295	New Perspective on Progressive GANs Distillation for One-class Novelty Detection	Computer Vision and Pattern Recognition (cs.CV)	Zhiwei Zhang, Yu Dong, Hanyu Peng, Shifeng Chen
2109.07396	Constraint based Knowledge Base Distillation in End-to-End Task Oriented Dialogs	Computation and Language (cs.CL)	Dinesh Raghu, Atishya Jain, Mausam, Sachindra Joshi
2109.07611	On-the-Fly Ensemble Pruning in Evolving Data Streams	Machine Learning (cs.LG)	Sanem Elbasi, Alican Büyükçakır, Hamed Bonab, Fazli Can
2109.07707	Dense Pruning of Pointwise Convolutions in the Frequency Domain	Computer Vision and Pattern Recognition (cs.CV)	Mark Buckler, Neil Adit, Yuwei Hu, Zhiru Zhang, Adrian Sampson
2109.07710	Exploiting Activation based Gradient Output Sparsity to Accelerate Backpropagation in CNNs	Machine Learning (cs.LG)	Anup Sarma, Sonali Singh, Huaipan Jiang, Ashutosh Pattnaik, Asit K Mishra, Vijaykrishnan Narayanan, Mahmut T Kandemir, Chita R Das
2109.07747	Neural-network acceleration of projection-based model-order-reduction for finite plasticity: Application to RVEs	Machine Learning (cs.LG)	S. Vijayaraghavan, L. Wu, L. Noels, S. P. A. Bordas, S. Natarajan, L. A. A. Beex
2109.07843	Label Assignment Distillation for Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Hailun Zhang
2109.07865	OMPQ: Orthogonal Mixed Precision Quantization	Machine Learning (cs.LG)	Yuexiao Ma, Taisong Jin, Xiawu Zheng, Yan Wang, Huixia Li, Guannan Jiang, Wei Zhang, Rongrong Ji
2109.07871	Resolution based Feature Distillation for Cross Resolution Person Re-Identification	Computer Vision and Pattern Recognition (cs.CV)	Asad Munir, Chengjin Lyu, Bart Goossens, Wilfried Philips, Christian Micheloni
2109.08090	DisUnknown: Distilling Unknown Factors for Disentanglement Learning	Machine Learning (cs.LG)	Sitao Xiang, Yuming Gu, Pengda Xiang, Menglei Chai, Hao Li, Yajie Zhao, Mingming He
2109.08331	Accelerating Offline Reinforcement Learning Application in Real-Time Bidding and Recommendation: Potential Use of Simulation	Machine Learning (cs.LG)	Haruka Kiyohara, Kosuke Kawakami, Yuta Saito
2109.08359	Distilling Linguistic Context for Language Model Compression	Computation and Language (cs.CL)	Geondo Park, Gyeongman Kim, Eunho Yang
2109.08814	Structured Pattern Pruning Using Regularization	Computation and Language (cs.CL)	Dongjun Park, Geung-Hee Lee
2109.08819	Toward Efficient Federated Learning in Multi-Channeled Mobile Edge Network with Layerd Gradient Compression	Machine Learning (cs.LG)	Haizhou Du, Xiaojie Feng, Qiao Xiang, Haoyu Liu
2109.08858	An Accelerated Variance-Reduced Conditional Gradient Sliding Algorithm for First-order and Zeroth-order Optimization	Machine Learning (cs.LG)	Xiyuan Wei, Bin Gu, Heng Huang
2109.08900	Dependency distance minimization predicts compression	Computation and Language (cs.CL)	Ramon Ferrer-i-Cancho, Carlos Gómez-Rodríguez
2109.09534	Accelerated Stochastic Gradient for Nonnegative Tensor Completion and Parallel Implementation	Signal Processing (eess.SP)	Ioanna Siaminou, Ioannis Marios Papagiannakos, Christos Kolomvakis, Athanasios P. Liavas
2109.09670	Reproducibility Study: Comparing Rewinding and Fine-tuning in Neural Network Pruning	Machine Learning (cs.LG)	Szymon Mikler (Uniwersytet Wrocławski)
2109.09847	Fast TreeSHAP: Accelerating SHAP Value Computation for Trees	Machine Learning (cs.LG)	Jilei Yang
2109.10021	Stabilizing Elastic Weight Consolidation method in practical ML tasks and using weight importances for neural network pruning	Machine Learning (cs.LG)	Alexey Kutalev, Alisa Lapina
2109.10147	Knowledge Distillation with Noisy Labels for Natural Language Understanding	Computation and Language (cs.CL)	Shivendra Bhardwaj, Abbas Ghaddar, Ahmad Rashid, Khalil Bibi, Chengyang Li, Ali Ghodsi, Philippe Langlais, Mehdi Rezagholizadeh
2109.10164	RAIL-KD: RAndom Intermediate Layer Mapping for Knowledge Distillation	Computation and Language (cs.CL)	Md Akmal Haidar, Nithin Anchuri, Mehdi Rezagholizadeh, Abbas Ghaddar, Philippe Langlais, Pascal Poupart
2109.10504	KD-VLP: Improving End-to-End Vision-and-Language Pretraining with Object Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yongfei Liu, Chenfei Wu, Shao-yen Tseng, Vasudev Lal, Xuming He, Nan Duan
2109.10591	High-dimensional Bayesian Optimization for CNN Auto Pruning with Clustering and Rollback	Machine Learning (cs.LG)	Jiandong Mu, Hanwei Fan, Wei Zhang
2109.10658	TACTIC: Joint Rate-Distortion-Accuracy Optimisation for Low Bitrate Compression	Computer Vision and Pattern Recognition (cs.CV)	Nikolina Kubiak, Simon Hadfield
2109.10795	Neural network relief: a pruning algorithm based on neural activity	Machine Learning (cs.LG)	Aleksandr Dekhovich, David M.J. Tax, Marcel H.F. Sluiter, Miguel A. Bessa
2109.11057	Weighted Low Rank Matrix Approximation and Acceleration	Machine Learning (stat.ML)	Elena Tuzhilina, Trevor Hastie
2109.11105	Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing	Computation and Language (cs.CL)	Haoyu He, Xingjian Shi, Jonas Mueller, Zha Sheng, Mu Li, George Karypis
2109.11168	Unified Signal Compression Using a GAN with Iterative Latent Representation Optimization	Signal Processing (eess.SP)	Bowen Liu, Changwoo Lee, Ang Cao, Hun-Seok Kim
2109.11295	Dynamic Knowledge Distillation for Pre-trained Language Models	Computation and Language (cs.CL)	Lei Li, Yankai Lin, Shuhuai Ren, Peng Li, Jie Zhou, Xu Sun
2109.11496	LGD: Label-guided Self-distillation for Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Peizhen Zhang, Zijian Kang, Tong Yang, Xiangyu Zhang, Nanning Zheng, Jian Sun
2109.12066	ZSD-YOLO: Zero-Shot YOLO Detection using Vision-Language KnowledgeDistillation	Computer Vision and Pattern Recognition (cs.CV)	Johnathan Xie, Shuai Zheng
2109.12497	Quantization for Distributed Optimization	Machine Learning (cs.LG)	Vineeth S
2109.12507	Partial to Whole Knowledge Distillation: Progressive Distilling Decomposed Knowledge Boosts Student Better	Computer Vision and Pattern Recognition (cs.CV)	Xuanyang Zhang, Xiangyu Zhang, Jian Sun
2109.12662	Improving Question Answering Performance Using Knowledge Distillation and Active Learning	Computation and Language (cs.CL)	Yasaman Boreshban, Seyed Morteza Mirbostani, Gholamreza Ghassem-Sani, Seyed Abolghasem Mirroshandel, Shahin Amiriparian
2109.12683	On the Prunability of Attention Heads in Multilingual BERT	Computation and Language (cs.CL)	Aakriti Budhraja, Madhura Pande, Pratyush Kumar, Mitesh M. Khapra
2109.12688	Nesterov Accelerated ADMM for Fast Diffeomorphic Image Registration	Computer Vision and Pattern Recognition (cs.CV)	Alexander Thorley, Xi Jia, Hyung Jin Chang, Boyang Liu, Karina Bunting, Victoria Stoll, Antonio de Marvao, Declan P. O'Regan, Georgios Gkoutos, Dipak Kotecha, Jinming Duan
2109.12701	Sparse Plus Low Rank Matrix Decomposition: A Discrete Optimization Approach	Machine Learning (stat.ML)	Dimitris Bertsimas, Ryan Cory-Wright, Nicholas A. G. Johnson
2109.12713	Provable Low Rank Plus Sparse Matrix Separation Via Nonconvex Regularizers	Machine Learning (stat.ML)	April Sagan, John E. Mitchell
2109.12758	Text to Insight: Accelerating Organic Materials Knowledge Extraction via Deep Learning	Computation and Language (cs.CL)	Xintong Zhao, Steven Lopez, Semion Saikin, Xiaohua Hu, Jane Greenberg
2109.12862	Deep Structured Instance Graph for Distilling Object Detectors	Computer Vision and Pattern Recognition (cs.CV)	Yixin Chen, Pengguang Chen, Shu Liu, Liwei Wang, Jiaya Jia
2109.12948	Understanding and Overcoming the Challenges of Efficient Transformer Quantization	Machine Learning (cs.LG)	Yelysei Bondarenko, Markus Nagel, Tijmen Blankevoort
2109.13059	Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations	Computation and Language (cs.CL)	Fangyu Liu, Yunlong Jiao, Jordan Massiah, Emine Yilmaz, Serhii Havrylov
2109.13087	Contextual Fine-to-Coarse Distillation for Coarse-grained Response Selection in Open-Domain Conversations	Computation and Language (cs.CL)	Wei Chen, Yeyun Gong, Can Xu, Huang Hu, Bolun Yao, Zhongyu Wei, Zhihao Fan, Xiaowu Hu, Bartuer Zhou, Biao Cheng, Daxin Jiang, Nan Duan
2109.13912	PDC-Net+: Enhanced Probabilistic Dense Correspondence Network	Computer Vision and Pattern Recognition (cs.CV)	Prune Truong, Martin Danelljan, Radu Timofte, Luc Van Gool
2109.13964	An Accelerated Stochastic Gradient for Canonical Polyadic Decomposition	Signal Processing (eess.SP)	Ioanna Siaminou, Athanasios P. Liavas
2109.14157	Hybrid Dynamic Contrast and Probability Distillation for Unsupervised Person Re-Id	Computer Vision and Pattern Recognition (cs.CV)	De Cheng, Jingyu Zhou, Nannan Wang, Xinbo Gao
2109.14611	Federated Self-Supervised Contrastive Learning via Ensemble Similarity Distillation	Machine Learning (cs.LG)	Haizhou Shi, Youcai Zhang, Zijin Shen, Siliang Tang, Yaqian Li, Yandong Guo, Yueting Zhuang
2109.14675	Data Sharing and Compression for Cooperative Networked Control	Machine Learning (cs.LG)	Jiangnan Cheng, Marco Pavone, Sachin Katti, Sandeep Chinchali, Ao Tang
2109.14707	BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining	Machine Learning (cs.LG)	Weizhe Hua, Yichi Zhang, Chuan Guo, Zhiru Zhang, G. Edward Suh
2109.14710	Convolutional Neural Network Compression through Generalized Kronecker Product Decomposition	Computer Vision and Pattern Recognition (cs.CV)	Marawan Gamal Abdel Hameed, Marzieh S. Tahaei, Ali Mosleh, Vahid Partovi Nia
2109.14878	Accelerating Fully Connected Neural Network on Optical Network-on-Chip (ONoC)	Distributed, Parallel, and Cluster Computing (cs.DC)	Fei Dai, Yawen Chen, Haibo Zhang, Zhiyi Huang
2109.14960	Prune Your Model Before Distill It	Machine Learning (cs.LG)	Jinhyuk Park, Albert No
2109.15014	Deep Neural Compression Via Concurrent Pruning and Self-Distillation	Machine Learning (cs.LG)	James O' Neill, Sourav Dutta, Haytham Assem
2109.15082	Towards Efficient Post-training Quantization of Pre-trained Language Models	Computation and Language (cs.CL)	Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Irwin King, Michael R. Lyu
2109.15196	Multilingual AMR Parsing with Noisy Knowledge Distillation	Computation and Language (cs.CL)	Deng Cai, Xin Li, Jackie Chun-Sing Ho, Lidong Bing, Wai Lam
2109.15200	Semi-tensor Product-based TensorDecomposition for Neural Network Compression	Machine Learning (cs.LG)	Hengling Zhao, Yipeng Liu, Xiaolin Huang, Ce Zhu
2110.00085	Accelerating Inverse Rendering By Using a GPU and Reuse of Light Paths	Computer Vision and Pattern Recognition (cs.CV)	Ido Czerninski, Yoav Y. Schechner
2110.00216	Beyond Neighbourhood-Preserving Transformations for Quantization-Based Unsupervised Hashing	Computer Vision and Pattern Recognition (cs.CV)	Sobhan Hemati, H.R. Tizhoosh
2110.00329	Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Zheng Li, Xiang Li, Lingfeng Yang, Jian Yang, Zhigeng Pan
2110.00625	Accelerate Distributed Stochastic Descent for Nonconvex Optimization with Momentum	Machine Learning (cs.LG)	Guojing Cong, Tianyi Liu
2110.01172	A New Acceleration Paradigm for Discrete CosineTransform and Other Fourier-Related Transforms	Distributed, Parallel, and Cluster Computing (cs.DC)	Zixuan Jiang, Jiaqi Gu, David Z. Pan
2110.01397	RED++ : Data-Free Pruning of Deep Neural Networks via Input Splitting and Output Merging	Machine Learning (cs.LG)	Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly
2110.01449	Artificial Neural Network and its Application Research Progress in Distillation	Machine Learning (cs.LG)	Jing Sun, Qi Tang
2110.01756	Bottom-up Hierarchical Classification Using Confusion-based Logit Compression	Machine Learning (cs.LG)	Tong Liang, Jim Davis, Roman Ilin
2110.01835	Compression, The Fermi Paradox and Artificial Super-Intelligence	Artificial Intelligence (cs.AI)	Michael Timothy Bennett
2110.01900	DistilHuBERT: Speech Representation Learning by Layer-wise Distillation of Hidden-unit BERT	Computation and Language (cs.CL)	Heng-Jui Chang, Shu-wen Yang, Hung-yi Lee
2110.02140	S2 Reducer: High-Performance Sparse Communication to Accelerate Distributed Deep Learning	Distributed, Parallel, and Cluster Computing (cs.DC)	Keshi Ge, Yongquan Fu, Zhiquan Lai, Xiaoge Deng, Dongsheng Li
2110.02291	FedDQ: Communication-Efficient Federated Learning with Descending Quantization	Machine Learning (cs.LG)	Linping Qu, Shenghui Song, Chi-Ying Tsui
2110.02432	Federated Distillation of Natural Language Understanding with Confident Sinkhorns	Computation and Language (cs.CL)	Rishabh Bhardwaj, Tushar Vaidya, Soujanya Poria
2110.02457	Solve Minimax Optimization by Anderson Acceleration	Machine Learning (cs.LG)	Huan He, Shifan Zhao, Yuanzhe Xi, Joyce C Ho, Yousef Saad
2110.02508	Online Hyperparameter Meta-Learning with Hypergradient Distillation	Machine Learning (cs.LG)	Hae Beom Lee, Hayeon Lee, Jaewoong Shin, Eunho Yang, Timothy Hospedales, Sung Ju Hwang
2110.02813	Accelerated First Order Methods for Variational Imaging	Computer Vision and Pattern Recognition (cs.CV)	Joseph Bartlett, Jinming Duan
2110.02861	8-bit Optimizers via Block-wise Quantization	Machine Learning (cs.LG)	Tim Dettmers, Mike Lewis, Sam Shleifer, Luke Zettlemoyer
2110.03036	The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation	Computation and Language (cs.CL)	Orevaoghene Ahia, Julia Kreutzer, Sara Hooker
2110.03155	Towards Understanding Distributional Reinforcement Learning: Regularization, Optimization, Acceleration and Sinkhorn Algorithm	Machine Learning (cs.LG)	Ke Sun, Yingnan Zhao, Yi Liu, Enze Shi, Yafei Wang, Aref Sadeghi, Xiaodong Yan, Bei Jiang, Linglong Kong
2110.03252	Layer-wise Pruning of Transformer Attention Heads for Efficient Language Modeling	Computation and Language (cs.CL)	Kyuhong Shim, Iksoo Choi, Wonyong Sung, Jungwook Choi
2110.03298	End-to-End Supermask Pruning: Learning to Prune Image Captioning Models	Computer Vision and Pattern Recognition (cs.CV)	Jia Huei Tan, Chee Seng Chan, Joon Huang Chuah
2110.03334	Knowledge Distillation for Neural Transducers from Large Self-Supervised Pre-trained Models	Audio and Speech Processing (eess.AS)	Xiaoyu Yang, Qiujia Li, Philip C. Woodland
2110.03742	Beyond Distillation: Task-level Mixture-of-Experts for Efficient Inference	Computation and Language (cs.CL)	Sneha Kudugunta, Yanping Huang, Ankur Bapna, Maxim Krikun, Dmitry Lepikhin, Minh-Thang Luong, Orhan Firat
2110.03780	A composable autoencoder-based iterative algorithm for accelerating numerical simulations	Machine Learning (cs.LG)	Rishikesh Ranade, Chris Hill, Haiyang He, Amir Maleki, Norman Chang, Jay Pathak
2110.03858	ABCP: Automatic Block-wise and Channel-wise Network Pruning via Joint Search	Computer Vision and Pattern Recognition (cs.CV)	Jiaqi Li, Haoran Li, Yaran Chen, Zixiang Ding, Nannan Li, Mingjun Ma, Zicheng Duan, Dongbing Zhao
2110.04252	LCS: Learning Compressible Subspaces for Adaptive Network Compression at Inference Time	Machine Learning (cs.LG)	Elvis Nunez, Maxwell Horton, Anish Prabhu, Anurag Ranjan, Ali Farhadi, Mohammad Rastegari
2110.04422	Theoretically Principled Deep RL Acceleration via Nearest Neighbor Function Approximation	Machine Learning (cs.LG)	Junhong Shen, Lin F. Yang
2110.04483	Visualizing the embedding space to explain the effect of knowledge distillation	Computer Vision and Pattern Recognition (cs.CV)	Hyun Seung Lee, Christian Wallraven
2110.04558	Unsupervised Representation Learning Meets Pseudo-Label Supervised Self-Distillation: A New Approach to Rare Disease Classification	Computer Vision and Pattern Recognition (cs.CV)	Jinghan Sun, Dong Wei, Kai Ma, Liansheng Wang, Yefeng Zheng
2110.04741	Enhance Long Text Understanding via Distilled Gist Detector from Abstractive Summarization	Computation and Language (cs.CL)	Yan Liu, Yazheng Yang
2110.04824	Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks	Computer Vision and Pattern Recognition (cs.CV)	Moshe Eliasof, Benjamin Bodner, Eran Treister
2110.04861	A Deep Learning Inference Scheme Based on Pipelined Matrix Multiplication Acceleration Design and Non-uniform Quantization	Machine Learning (cs.LG)	Yuyang Zhang, Dik Hin Leung, Min Guo, Yijia Xiao, Haoyue Liu, Yunfei Li, Jiyuan Zhang, Guan Wang, Zhen Chen
2110.04869	NViT: Vision Transformer Compression and Parameter Redistribution	Computer Vision and Pattern Recognition (cs.CV)	Huanrui Yang, Hongxu Yin, Pavlo Molchanov, Hai Li, Jan Kautz
2110.05242	Accelerating Multi-Objective Neural Architecture Search by Random-Weight Evaluation	Machine Learning (cs.LG)	Shengran Hu, Ran Cheng, Cheng He, Zhichao Lu, Jing Wang, Miao Zhang
2110.05667	Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks	Machine Learning (cs.LG)	Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
2110.05722	LightSeq2: Accelerated Training for Transformer-based Models on GPUs	Computation and Language (cs.CL)	Xiaohui Wang, Ying Xiong, Xian Qian, Yang Wei, Lei Li, Mingxuan Wang
2110.05731	Topic Scene Graph Generation by Attention Distillation from Caption	Computer Vision and Pattern Recognition (cs.CV)	W. Wang, R. Wang, X. Chen
2110.05837	Explicit CSI Feedback Compression via Learned Approximate Message Passing	Signal Processing (eess.SP)	Benedikt Groß, Rana Ahmed Salem, Thorsten Wild, Gerhard Wunder
2110.06290	Scalable Consistency Training for Graph Neural Networks via Self-Ensemble Self-Distillation	Machine Learning (cs.LG)	Cole Hawkins, Vassilis N. Ioannidis, Soji Adeshina, George Karypis
2110.06381	Meta Learning Low Rank Covariance Factors for Energy-Based Deterministic Uncertainty	Machine Learning (stat.ML)	Jeffrey Ryan Willette, Hae Beom Lee, Juho Lee, Sung Ju Hwang
2110.06483	False Negative Distillation and Contrastive Learning for Personalized Outfit Recommendation	Information Retrieval (cs.IR)	Seongjae Kim, Jinseok Seol, Holim Lim, Sang-goo Lee
2110.06554	Towards Mixed-Precision Quantization of Neural Networks via Constrained Optimization	Computer Vision and Pattern Recognition (cs.CV)	Weihan Chen, Peisong Wang, Jian Cheng
2110.07007	Out-of-Distribution Robustness in Deep Learning Compression	Machine Learning (cs.LG)	Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti
2110.07178	Symbolic Knowledge Distillation: from General Language Models to Commonsense Models	Computation and Language (cs.CL)	Peter West, Chandra Bhagavatula, Jack Hessel, Jena D. Hwang, Liwei Jiang, Ronan Le Bras, Ximing Lu, Sean Welleck, Yejin Choi
2110.07595	Compressibility of Distributed Document Representations	Computation and Language (cs.CL)	Blaž Škrlj, Matej Petkovič
2110.07809	PTQ-SL: Exploring the Sub-layerwise Post-training Quantization	Computer Vision and Pattern Recognition (cs.CV)	Zhihang Yuan, Yiqi Chen, Chenhao Xue, Chenguang Zhang, Qiankun Wang, Guangyu Sun
2110.07936	Bridging the Gap: Cross-Lingual Summarization with Compression Rate	Computation and Language (cs.CL)	Yu Bai, Heyan Huang, Kai Fan, Yang Gao, Zewen Chi, Boxing Chen
2110.08013	Joint Channel and Weight Pruning for Model Acceleration on Moblie Devices	Computer Vision and Pattern Recognition (cs.CV)	Tianli Zhao, Xi Sheryl Zhang, Wentao Zhu, Jiaxing Wang, Sen Yang, Ji Liu, Jian Cheng
2110.08152	Kronecker Decomposition for GPT Compression	Computation and Language (cs.CL)	Ali Edalati, Marzieh Tahaei, Ahmad Rashid, Vahid Partovi Nia, James J. Clark, Mehdi Rezagholizadeh
2110.08190	Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm	Computation and Language (cs.CL)	Shaoyi Huang, Dongkuan Xu, Ian E.H. Yen, Sung-en Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Hang Liu, Caiwen Ding
2110.08232	Fire Together Wire Together: A Dynamic Pruning Approach with Self-Supervised Mask Prediction	Computer Vision and Pattern Recognition (cs.CV)	Sara Elkerdawy, Mostafa Elhoushi, Hong Zhang, Nilanjan Ray
2110.08270	From Multimodal to Unimodal Attention in Transformers using Knowledge Distillation	Machine Learning (cs.LG)	Dhruv Agarwal, Tanay Agrawal, Laura M. Ferrari, François Bremond
2110.08271	Training Deep Neural Networks with Joint Quantization and Pruning of Weights and Activations	Machine Learning (cs.LG)	Xinyu Zhang, Ian Colbert, Ken Kreutz-Delgado, Srinjoy Das
2110.08350	Differentiable Network Pruning for Microcontrollers	Machine Learning (cs.LG)	Edgar Liberis, Nicholas D. Lane
2110.08450	Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining	Machine Learning (cs.LG)	Tim Kaler, Nickolas Stathas, Anne Ouyang, Alexandros-Stavros Iliopoulos, Tao B. Schardl, Charles E. Leiserson, Jie Chen
2110.08460	A Short Study on Compressing Decoder-Based Language Models	Computation and Language (cs.CL)	Tianda Li, Yassir El Mesbahi, Ivan Kobyzev, Ahmad Rashid, Atif Mahmud, Nithin Anchuri, Habib Hajimolahoseini, Yang Liu, Mehdi Rezagholizadeh
2110.08532	Pro-KD: Progressive Distillation by Following the Footsteps of the Teacher	Computation and Language (cs.CL)	Mehdi Rezagholizadeh, Aref Jafari, Puneeth Salad, Pranav Sharma, Ali Saheb Pasand, Ali Ghodsi
2110.08536	Sparse Distillation: Speeding Up Text Classification by Using Bigger Models	Computation and Language (cs.CL)	Qinyuan Ye, Madian Khabsa, Mike Lewis, Sinong Wang, Xiang Ren, Aaron Jaech
2110.08551	HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression	Computation and Language (cs.CL)	Chenhe Dong, Yaliang Li, Ying Shen, Minghui Qiu
2110.08558	Neural Network Pruning Through Constrained Reinforcement Learning	Computer Vision and Pattern Recognition (cs.CV)	Shehryar Malik, Muhammad Umair Haider, Omer Iqbal, Murtaza Taj
2110.08679	An Acceleration Method Based on Deep Learning and Multilinear Feature Space	Computer Vision and Pattern Recognition (cs.CV)	Michel Vinagreiro Edson Kitani Armando Lagana Leopoldo Yoshioka
2110.08727	Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation	Machine Learning (cs.LG)	Shichang Zhang, Yozen Liu, Yizhou Sun, Neil Shah
2110.08745	Reminding the Incremental Language Model via Data-Free Self-Distillation	Computation and Language (cs.CL)	Han Wang, Ruiliu Fu, Chengzhang Li, Xuejun Zhang, Jun Zhou, Yonghong Yan
2110.08764	S-Cyc: A Learning Rate Schedule for Iterative Pruning of ReLU-based Networks	Machine Learning (cs.LG)	Shiyu Liu, Chong Min John Tan, Mehul Motani
2110.08828	Compression-aware Projection with Greedy Dimension Reduction for Convolutional Neural Network Activations	Computer Vision and Pattern Recognition (cs.CV)	Yu-Shan Tai, Chieh-Fang Teng, Cheng-Yang Chang, An-Yeu Wu
2110.08896	Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization	Machine Learning (cs.LG)	Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, Bo Pan, Shangling Jui, Bei Jiang, Linglong Kong
2110.08902	Green Simulation Assisted Policy Gradient to Accelerate Stochastic Process Control	Machine Learning (cs.LG)	Hua Zheng, Wei Xie, M. Ben Feng
2110.08919	Low-Precision Quantization for Efficient Nearest Neighbor Search	Information Retrieval (cs.IR)	Anthony Ko, Iman Keivanloo, Vihan Lakshman, Eric Schkufza
2110.09109	Patch-Based Deep Autoencoder for Point Cloud Geometry Compression	Computer Vision and Pattern Recognition (cs.CV)	Kang You, Pan Gao
2110.09132	EmbRace: Accelerating Sparse Communication for Distributed Training of NLP Neural Networks	Machine Learning (cs.LG)	Shengwei Li, Zhiquan Lai, Dongsheng Li, Xiangyu Ye, Yabo Duan
2110.09195	Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Yikai Wang, Yi Yang, Fuchun Sun, Anbang Yao
2110.09241	Video Coding for Machine: Compact Visual Representation Compression for Intelligent Collaborative Analytics	Computer Vision and Pattern Recognition (cs.CV)	Wenhan Yang, Haofeng Huang, Yueyu Hu, Ling-Yu Duan, Jiaying Liu
2110.09541	Wideband and Entropy-Aware Deep Soft Bit Quantization	Signal Processing (eess.SP)	Marius Arvinte, Jonathan I. Tamir
2110.09674	Adaptive Distillation: Aggregating Knowledge from Multiple Paths for Efficient Distillation	Computer Vision and Pattern Recognition (cs.CV)	Sumanth Chennupati, Mohammad Mahdi Kamani, Zhongwei Cheng, Lin Chen
2110.09677	Accelerated Graph Learning from Smooth Signals	Machine Learning (cs.LG)	Seyed Saman Saboksayr, Gonzalo Mateos
2110.09953	Minimal Compression of a Radio-Frequency Pulse	Signal Processing (eess.SP)	W. J. Szajnowski
2110.10149	Continuous Control with Action Quantization from Demonstrations	Machine Learning (cs.LG)	Robert Dadashi, Léonard Hussenot, Damien Vincent, Sertan Girgin, Anton Raichuk, Matthieu Geist, Olivier Pietquin
2110.10423	ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-cost Proxies	Machine Learning (cs.LG)	Yu Shen, Yang Li, Jian Zheng, Wentao Zhang, Peng Yao, Jixiang Li, Sen Yang, Ji Liu, Bin Cui
2110.10429	Knowledge distillation from language model to acoustic model: a hierarchical multi-task learning approach	Machine Learning (cs.LG)	Mun-Hak Lee, Joon-Hyuk Chang
2110.10765	Accelerating quantum many-body configuration interaction with directives	Distributed, Parallel, and Cluster Computing (cs.DC)	Brandon Cook, Patrick J. Fasano, Pieter Maris, Chao Yang, Dossay Oryspayev
2110.10864	Class-Discriminative CNN Compression	Computer Vision and Pattern Recognition (cs.CV)	Yuchen Liu, David Wentzlaff, S.Y. Kung
2110.10876	Evolving Transferable Pruning Functions	Computer Vision and Pattern Recognition (cs.CV)	Yuchen Liu, S.Y. Kung, David Wentzlaff
2110.10921	CATRO: Channel Pruning via Class-Aware Trace Ratio Optimization	Machine Learning (cs.LG)	Wenzheng Hu, Ning Liu, Zhengping Che, Mingyang Li, Jian Tang, Changshui Zhang, Jianqiang Wang
2110.11023	Augmenting Knowledge Distillation With Peer-To-Peer Mutual Learning For Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Usma Niyaz, Deepti R. Bathula
2110.11150	Towards strong pruning for lottery tickets with non-zero biases	Machine Learning (cs.LG)	Jonas Fischer, Rebekka Burkholz
2110.11226	Accelerating Genetic Programming using GPUs	Neural and Evolutionary Computing (cs.NE)	Vimarsh Sathia (1), Venkataramana Ganesh (2), Shankara Rao Thejaswi Nanditale (2) ((1) Indian Institute of Technology Madras, (2) NVIDIA Corporation)
2110.11299	Transformer Acceleration with Dynamic Sparse Attention	Machine Learning (cs.LG)	Liu Liu, Zheng Qu, Zhaodong Chen, Yufei Ding, Yuan Xie
2110.11395	SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning	Machine Learning (cs.LG)	Manuel Nonnenmacher, Thomas Pfeil, Ingo Steinwart, David Reeb
2110.11794	Federated Unlearning via Class-Discriminative Pruning	Computer Vision and Pattern Recognition (cs.CV)	Junxiao Wang, Song Guo, Xin Xie, Heng Qi
2110.11804	Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded learning	Machine Learning (stat.ML)	Soufiane Hayou, Bobby He, Gintare Karolina Dziugaite
2110.11887	C$^{4}$Net: Contextual Compression and Complementary Combination Network for Salient Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Hazarapet Tunanyan
2110.12007	When to Prune? A Policy towards Early Structural Pruning	Computer Vision and Pattern Recognition (cs.CV)	Maying Shen, Pavlo Molchanov, Hongxu Yin, Jose M. Alvarez
2110.12072	How and When Adversarial Robustness Transfers in Knowledge Distillation?	Machine Learning (cs.LG)	Rulin Shao, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh
2110.12308	A Layer-wise Adversarial-aware Quantization Optimization for Improving Robustness	Machine Learning (cs.LG)	Chang Song, Riya Ranjan, Hai Li
2110.12348	Convolutional Autoencoder-Based Phase Shift Feedback Compression for Intelligent Reflecting Surface-Assisted Wireless Systems	Signal Processing (eess.SP)	Xianhua Yu, Dong Li, Yongjun Xu, Ying-Chang Liang
2110.12387	Task-Based Graph Signal Compression	Signal Processing (eess.SP)	Pei Li, Nir Shlezinger, Haiyang Zhang, Baoyun Wang, Yonina C. Eldar
2110.12477	Exploring Gradient Flow Based Saliency for DNN Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Xinyu Liu, Baopu Li, Zhen Chen, Yixuan Yuan
2110.12478	Deep Asymmetric Hashing with Dual Semantic Regression and Class Structure Quantization	Computer Vision and Pattern Recognition (cs.CV)	Jianglin Lu, Hailing Wang, Jie Zhou, Mengfan Yan, Jiajun Wen
2110.12516	X-Distill: Improving Self-Supervised Monocular Depth via Cross-Task Distillation	Computer Vision and Pattern Recognition (cs.CV)	Hong Cai, Janarbek Matai, Shubhankar Borse, Yizhe Zhang, Amin Ansari, Fatih Porikli
2110.12606	MUSE: Feature Self-Distillation with Mutual Information and Self-Information	Computer Vision and Pattern Recognition (cs.CV)	Yu Gong, Ye Yu, Gaurav Mittal, Greg Mori, Mei Chen
2110.12621	Accelerate 3D Object Processing via Spectral Layout	Computer Vision and Pattern Recognition (cs.CV)	Yongyu Wang
2110.12717	A Distillation Learning Model of Adaptive Structural Deep Belief Network for AffectNet: Facial Expression Image Database	Computer Vision and Pattern Recognition (cs.CV)	Takumi Ichimura, Shin Kamada
2110.12724	Instance-Conditional Knowledge Distillation for Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Zijian Kang, Peizhen Zhang, Xiangyu Zhang, Jian Sun, Nanning Zheng
2110.12844	Network compression and faster inference using spatial basis filters	Computer Vision and Pattern Recognition (cs.CV)	Roy Miles, Krystian Mikolajczyk
2110.12952	Accelerating Compact Fractals with Tensor Core GPUs	Distributed, Parallel, and Cluster Computing (cs.DC)	Felipe A. Quezada, Cristóbal A. Navarro
2110.13229	Distributionally Robust Recurrent Decoders with Random Network Distillation	Machine Learning (cs.LG)	Antonio Valerio Miceli-Barone, Alexandra Birch, Rico Sennrich
2110.13368	OpenACC Acceleration of an Agent-Based Biological Simulation Framework	Distributed, Parallel, and Cluster Computing (cs.DC)	Matt Stack, Paul Macklin, Robert Searles, Sunita Chandrasekaran
2110.13422	Relay Variational Inference: A Method for Accelerated Encoderless VI	Machine Learning (cs.LG)	Amir Zadeh, Santiago Benoit, Louis-Philippe Morency
2110.13471	Response-based Distillation for Incremental Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Tao Feng, Mang Wang
2110.13506	A DPDK-Based Acceleration Method for Experience Sampling of Distributed Reinforcement Learning	Distributed, Parallel, and Cluster Computing (cs.DC)	Masaki Furukawa, Hiroki Matsutani
2110.13541	Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes	Machine Learning (cs.LG)	Sanghyun Hong, Michael-Andrei Panaitescu-Liess, Yiğitcan Kaya, Tudor Dumitraş
2110.13674	C$^2$SP-Net: Joint Compression and Classification Network for Epilepsy Seizure Prediction	Machine Learning (cs.LG)	Di Wu, Yi Shi, Ziyu Wang, Jie Yang, Mohamad Sawan
2110.13981	CHIP: CHannel Independence-based Pruning for Compact Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Yang Sui, Miao Yin, Yi Xie, Huy Phan, Saman Zonouz, Bo Yuan
2110.14205	FedPrune: Towards Inclusive Federated Learning	Machine Learning (cs.LG)	Muhammad Tahir Munir, Muhammad Mustansar Saeed, Mahad Ali, Zafar Ayyub Qazi, Ihsan Ayyub Qazi
2110.14215	Beyond Classification: Knowledge Distillation using Multi-Object Impressions	Computer Vision and Pattern Recognition (cs.CV)	Gaurav Kumar Nayak, Monish Keswani, Sharan Seshadri, Anirban Chakraborty
2110.14363	VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization	Machine Learning (cs.LG)	Mucong Ding, Kezhi Kong, Jingling Li, Chen Zhu, John P Dickerson, Furong Huang, Tom Goldstein
2110.14430	Adversarial Neuron Pruning Purifies Backdoored Deep Models	Machine Learning (cs.LG)	Dongxian Wu, Yisen Wang
2110.14439	Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme	Computer Vision and Pattern Recognition (cs.CV)	Shaojie Li, Jie Wu, Xuefeng Xiao, Fei Chao, Xudong Mao, Rongrong Ji
2110.14459	Accelerating Gradient-based Meta Learner	Machine Learning (cs.LG)	Varad Pimpalkhute, Amey Pandit, Mayank Mishra, Rekha Singhal
2110.14813	Stable Anderson Acceleration for Deep Learning	Machine Learning (cs.LG)	Massimiliano Lupo Pasini, Junqi Yin, Viktor Reshniak, Miroslav Stoyanov
2110.14856	An Operator Theoretic Perspective on Pruning Deep Neural Networks	Machine Learning (cs.LG)	William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
2110.15094	Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data	Machine Learning (cs.LG)	Gongfan Fang, Yifan Bao, Jie Song, Xinchao Wang, Donglin Xie, Chengchao Shen, Mingli Song
2110.15192	RGP: Neural Network Pruning through Its Regular Graph Structure	Machine Learning (cs.LG)	Zhuangzhi Chen, Jingyang Xiang, Yao Lu, Qi Xuan, Xiaoniu Yang
2110.15210	Towards Model Agnostic Federated Learning Using Knowledge Distillation	Machine Learning (cs.LG)	Andrei Afonin, Sai Praneeth Karimireddy
2110.15225	Pruning Attention Heads of Transformer Models Using A* Search: A Novel Approach to Compress Big NLP Architectures	Computation and Language (cs.CL)	Archit Parnami, Rahul Singh, Tarun Joshi
2110.15360	Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives	Machine Learning (cs.LG)	Murtaza Dalal, Deepak Pathak, Ruslan Salakhutdinov
2110.15362	BitTrain: Sparse Bitmap Compression for Memory-Efficient Training on the Edge	Machine Learning (cs.LG)	Abdelrahman Hosny, Marina Neseem, Sherief Reda
2110.15644	Gabor filter incorporated CNN for compression	Computer Vision and Pattern Recognition (cs.CV)	Akihiro Imamura, Nana Arizumi
2110.15705	Distilling Relation Embeddings from Pre-trained Language Models	Computation and Language (cs.CL)	Asahi Ushio, Jose Camacho-Collados, Steven Schockaert
2110.15946	Estimating and Maximizing Mutual Information for Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Aman Shrivastava, Yanjun Qi, Vicente Ordonez
2111.00153	RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions	Machine Learning (cs.LG)	Sung-En Chang, Yanyu Li, Mengshu Sun, Weiwen Jiang, Sijia Liu, Yanzhi Wang, Xue Lin
2111.00230	Magic Pyramid: Accelerating Inference with Early Exiting and Token Pruning	Computation and Language (cs.CL)	Xuanli He, Iman Keivanloo, Yi Xu, Xiang He, Belinda Zeng, Santosh Rajagopalan, Trishul Chilimbi
2111.00406	PANet: Perspective-Aware Network with Dynamic Receptive Fields and Self-Distilling Supervision for Crowd Counting	Computer Vision and Pattern Recognition (cs.CV)	Xiaoshuang Chen, Yiru Zhao, Yu Qin, Fei Jiang, Mingyuan Tao, Xiansheng Hua, Hongtao Lu
2111.00465	DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning	Machine Learning (cs.LG)	Robert Hönig, Yiren Zhao, Robert Mullins
2111.00643	Learning Distilled Collaboration Graph for Multi-Agent Perception	Computer Vision and Pattern Recognition (cs.CV)	Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng, Wenjun Zhang
2111.00674	Distilling Object Detectors with Feature Richness	Computer Vision and Pattern Recognition (cs.CV)	Zhixing Du, Rui Zhang, Ming Chang, Xishan Zhang, Shaoli Liu, Tianshi Chen, Yunji Chen
2111.00965	iFlow: Numerically Invertible Flows for Efficient Lossless Compression via a Uniform Coder	Machine Learning (cs.LG)	Shifeng Zhang, Ning Kang, Tom Ryder, Zhenguo Li
2111.01026	Introspective Distillation for Robust Question Answering	Computer Vision and Pattern Recognition (cs.CV)	Yulei Niu, Hanwang Zhang
2111.01135	Arch-Net: Model Distillation for Architecture Agnostic Model Deployment	Machine Learning (cs.LG)	Weixin Xu, Zipeng Feng, Shuangkang Fang, Song Yuan, Yi Yang, Shuchang Zhou
2111.01662	OSOA: One-Shot Online Adaptation of Deep Generative Models for Lossless Compression	Machine Learning (cs.LG)	Chen Zhang, Shifeng Zhang, Fabio Maria Carlucci, Zhenguo Li
2111.01684	Rethinking the Knowledge Distillation From the Perspective of Model Calibration	Computer Vision and Pattern Recognition (cs.CV)	Lehan Yang, Jincen Song
2111.01697	Low-Rank+Sparse Tensor Compression for Neural Networks	Machine Learning (cs.LG)	Cole Hawkins, Haichuan Yang, Meng Li, Liangzhen Lai, Vikas Chandra
2111.02100	Conditional Attention Networks for Distilling Knowledge Graphs in Recommendation	Machine Learning (cs.LG)	Ke Tu, Peng Cui, Daixin Wang, Zhiqiang Zhang, Jun Zhou, Yuan Qi, Wenwu Zhu
2111.02331	LTD: Low Temperature Distillation for Robust Adversarial Training	Computer Vision and Pattern Recognition (cs.CV)	Erh-Chung Chen, Che-Rung Lee
2111.02399	Learning Pruned Structure and Weights Simultaneously from Scratch: an Attention based Approach	Machine Learning (cs.LG)	Qisheng He, Ming Dong, Loren Schwiebert, Weisong Shi
2111.02625	Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples	Machine Learning (cs.LG)	Kanghyun Choi, Deokki Hong, Noseong Park, Youngsok Kim, Jinho Lee
2111.03065	Safe and Practical GPU Acceleration in TrustZone	Distributed, Parallel, and Cluster Computing (cs.DC)	Heejin Park, Felix Xiaozhu Lin
2111.03201	Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative Models	Machine Learning (cs.LG)	Daniel Bogdoll, Johannes Jestram, Jonas Rauch, Christin Scheib, Moritz Wittig, J. Marius Zöllner
2111.03267	Distilling Heterogeneity: From Explanations of Heterogeneous Treatment Effect Models to Interpretable Policies	Machine Learning (cs.LG)	Han Wu, Sarah Tan, Weiwei Li, Mia Garrard, Adam Obeng, Drew Dimmery, Shaun Singh, Hanson Wang, Daniel Jiang, Eytan Bakshy
2111.03555	AUTOKD: Automatic Knowledge Distillation Into A Student Architecture Family	Machine Learning (cs.LG)	Roy Henha Eyono, Fabio Maria Carlucci, Pedro M Esperança, Binxin Ru, Phillip Torr
2111.03664	Oracle Teacher: Towards Better Knowledge Distillation	Machine Learning (cs.LG)	Ji Won Yoon, Hyung Yong Kim, Hyeonseung Lee, Sunghwan Ahn, Nam Soo Kim
2111.03759	MQBench: Towards Reproducible and Deployable Model Quantization Benchmark	Machine Learning (cs.LG)	Yuhang Li, Mingzhu Shen, Jian Ma, Yan Ren, Mingxin Zhao, Qi Zhang, Ruihao Gong, Fengwei Yu, Junjie Yan
2111.03842	Class Token and Knowledge Distillation for Multi-head Self-Attention Speaker Verification Systems	Audio and Speech Processing (eess.AS)	Victoria Mingote, Antonio Miguel, Alfonso Ortega, Eduardo Lleida
2111.04033	Positivity Validation Detection and Explainability via Zero Fraction Multi-Hypothesis Testing and Asymmetrically Pruned Decision Trees	Machine Learning (cs.LG)	Guy Wolf, Gil Shabat, Hanan Shteingart
2111.04840	Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods	Machine Learning (cs.LG)	Wenqing Zheng, Edward W Huang, Nikhil Rao, Sumeet Katariya, Zhangyang Wang, Karthik Subbian
2111.04946	Graph-Based Depth Denoising & Dequantization for Point Cloud Enhancement	Computer Vision and Pattern Recognition (cs.CV)	Xue Zhang, Gene Cheung, Jiahao Pang, Yash Sanghvi, Abhiram Gnanasambandam, Stanley H. Chan
2111.04964	On Representation Knowledge Distillation for Graph Neural Networks	Machine Learning (cs.LG)	Chaitanya K. Joshi, Fayao Liu, Xu Xun, Jie Lin, Chuan-Sheng Foo
2111.04993	Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition	Computer Vision and Pattern Recognition (cs.CV)	Kai Wang, Xialei Liu, Andy Bagdanov, Luis Herranz, Shangling Jui, Joost van de Weijer
2111.05073	MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps	Machine Learning (cs.LG)	Muhammad Awais, Fengwei Zhou, Chuanlong Xie, Jiawei Li, Sung-Ho Bae, Zhenguo Li
2111.05471	Analysis of PDE-based binarization model for degraded document images	Computer Vision and Pattern Recognition (cs.CV)	Uche A. Nnolim
2111.05694	LSP : Acceleration and Regularization of Graph Neural Networks via Locality Sensitive Pruning of Graphs	Machine Learning (cs.LG)	Eitan Kosman, Joel Oren, Dotan Di Castro
2111.05754	Prune Once for All: Sparse Pre-Trained Language Models	Computation and Language (cs.CL)	Ofir Zafrir, Ariel Larey, Guy Boudoukh, Haihao Shen, Moshe Wasserblat
2111.05950	Self-Compression in Bayesian Neural Networks	Machine Learning (cs.LG)	Giuseppina Carannante, Dimah Dera, Ghulam Rasool, Nidhal C. Bouaynaya
2111.06146	FedGreen: Federated Learning with Fine-Grained Gradient Compression for Green Mobile Edge Computing	Machine Learning (cs.LG)	Peichun Li, Xumin Huang, Miao Pan, Rong Yu
2111.06383	Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation	Machine Learning (cs.LG)	I-Chun Arthur Liu, Shagun Uppal, Gaurav S. Sukhatme, Joseph J. Lim, Peter Englert, Youngwoon Lee
2111.06572	A new technique for compression of data sets	Signal Processing (eess.SP)	Anatoli Torokhti
2111.06781	Q-Learning for MDPs with General Spaces: Convergence and Near Optimality via Quantization under Weak Continuity	Machine Learning (cs.LG)	Ali Devran Kara, Naci Saldi, Serdar Yüksel
2111.06945	Learning Interpretation with Explainable Knowledge Distillation	Machine Learning (cs.LG)	Raed Alharbi, Minh N. Vu, My T. Thai
2111.07046	Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization	Machine Learning (cs.LG)	Cheng-Chou Lan
2111.07047	Facial Landmark Points Detection Using Knowledge Distillation-Based Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Ali Pourramezan Fard, Mohammad H. Mahoor
2111.07239	Robust and Accurate Object Detection via Self-Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Weipeng Xu, Pengzhi Chu, Renhao Xie, Xiongziyan Xiao, Hongcheng Huang
2111.07599	DNN gradient lossless compression: Can GenNorm be the answer?	Machine Learning (cs.LG)	Zhong-Jing Chen, Eduin E. Hernandez, Yu-Chih Huang, Stefano Rini
2111.07941	Distribution Compression in Near-linear Time	Machine Learning (stat.ML)	Abhishek Shetty, Raaz Dwivedi, Lester Mackey
2111.08275	Deep Distilling: automated code generation using explainable deep learning	Machine Learning (cs.LG)	Paul J. Blazek, Kesavan Venkatesh, Milo M. Lin
2111.08277	Wyner-Ziv Gradient Compression for Federated Learning	Machine Learning (cs.LG)	Kai Liang, Huiru Zhong, Haoning Chen, Youlong Wu
2111.08577	Neuron-based Pruning of Deep Neural Networks with Better Generalization using Kronecker Factored Curvature Approximation	Machine Learning (cs.LG)	Abdolghani Ebrahimi, Diego Klabjan
2111.08913	Long-Tailed Multi-Label Retinal Diseases Recognition Using Hierarchical Information and Hybrid Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Lie Ju, Xin Wang, Zhen Yu, Lin Wang, Xin Zhao, Zongyuan Ge
2111.08920	Reconstruction-Computation-Quantization (RCQ): A Paradigm for Low Bit Width LDPC Decoding	Signal Processing (eess.SP)	Linfang Wang, Caleb Terrill, Maximilian Stark, Zongwang Li, Sean Chen, Chester Hulse, Calvin Kuo, Richard Wesel, Gerhard Bauch, Rekha Pitchumani
2111.09034	Using Convolutional Neural Networks to Detect Compression Algorithms	Computer Vision and Pattern Recognition (cs.CV)	Shubham Bharadwaj
2111.09078	Green CWS: Extreme Distillation and Efficient Decode Method Towards Industrial Application	Artificial Intelligence (cs.AI)	Yulan Hu, Yong Liu
2111.09136	IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization	Computer Vision and Pattern Recognition (cs.CV)	Yunshan Zhong, Mingbao Lin, Gongrui Nan, Jianzhuang Liu, Baochang Zhang, Yonghong Tian, Rongrong Ji
2111.09499	Dynamically pruning segformer for efficient semantic segmentation	Computer Vision and Pattern Recognition (cs.CV)	Haoli Bai, Hongda Mao, Dinesh Nair
2111.09547	QGTC: Accelerating Quantized Graph Neural Networks via GPU Tensor Core	Distributed, Parallel, and Cluster Computing (cs.DC)	Yuke Wang, Boyuan Feng, Yufei Ding
2111.09562	COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression	Artificial Intelligence (cs.AI)	Sian Jin, Chengming Zhang, Xintong Jiang, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao
2111.09635	Automatic Neural Network Pruning that Efficiently Preserves the Model Accuracy	Computer Vision and Pattern Recognition (cs.CV)	Thibault Castells, Seul-Ki Yeom
2111.09692	SUB-Depth: Self-distillation and Uncertainty Boosting Self-supervised Monocular Depth Estimation	Computer Vision and Pattern Recognition (cs.CV)	Hang Zhou, Sarah Taylor, David Greenwood
2111.10105	Fast Spatio-temporal Compression of Dynamic 3D Meshes	Signal Processing (eess.SP)	Gerasimos Arvanitis, Aris S. Lalos, Konstantinos Moustakas
2111.10320	Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression	Computer Vision and Pattern Recognition (cs.CV)	Yuezhou Sun, Wenlong Zhao, Lijun Zhang, Xiao Liu, Hui Guan, Matei Zaharia
2111.10633	Sparse Tensor-based Multiscale Representation for Point Cloud Geometry Compression	Computer Vision and Pattern Recognition (cs.CV)	Jianqiang Wang, Dandan Ding, Zhu Li, Xiaoxing Feng, Chuntong Cao, Zhan Ma
2111.10957	Hierarchical Knowledge Distillation for Dialogue Sequence Labeling	Computation and Language (cs.CL)	Shota Orihashi, Yoshihiro Yamazaki, Naoki Makishima, Mana Ihori, Akihiko Takashima, Tomohiro Tanaka, Ryo Masumura
2111.10985	Efficient Non-Compression Auto-Encoder for Driving Noise-based Road Surface Anomaly Detection	Computer Vision and Pattern Recognition (cs.CV)	YeongHyeon Park, JongHee Jung
2111.11251	Machine Learning-Based Soft Sensors for Vacuum Distillation Unit	Machine Learning (cs.LG)	Kamil Oster, Stefan Güttel, Lu Chen, Jonathan L. Shapiro, Megan Jobson
2111.11581	Automatic Mapping of the Best-Suited DNN Pruning Schemes for Real-Time Mobile Acceleration	Machine Learning (cs.LG)	Yifan Gong, Geng Yuan, Zheng Zhan, Wei Niu, Zhengang Li, Pu Zhao, Yuxuan Cai, Sijia Liu, Bin Ren, Xue Lin, Xulong Tang, Yanzhi Wang
2111.11632	Lossless Compression with Probabilistic Circuits	Machine Learning (cs.LG)	Anji Liu, Stephan Mandt, Guy Van den Broeck
2111.11747	Semi-Online Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Zhiqiang Liu, Yanxia Liu, Chengkai Huang
2111.11802	Pruning Self-attentions into Convolutional Layers in Single Path	Computer Vision and Pattern Recognition (cs.CV)	Haoyu He, Jing Liu, Zizheng Pan, Jianfei Cai, Jing Zhang, Dacheng Tao, Bohan Zhuang
2111.11837	Focal and Global Knowledge Distillation for Detectors	Computer Vision and Pattern Recognition (cs.CV)	Zhendong Yang, Zhe Li, Xiaohu Jiang, Yuan Gong, Zehuan Yuan, Danpei Zhao, Chun Yuan
2111.11899	Results of improved fractional/integer order PDE-based binarization model	Computer Vision and Pattern Recognition (cs.CV)	Uche A. Nnolim
2111.11924	A Variant RSA Acceleration with Parallelization	Distributed, Parallel, and Cluster Computing (cs.DC)	Jun-jie Liu, Kang-Too Tsang, Yu-Hui Deng
2111.11986	HERO: Hessian-Enhanced Robust Optimization for Unifying and Improving Generalization and Quantization Performance	Machine Learning (cs.LG)	Huanrui Yang, Xiaoxuan Yang, Neil Zhenqiang Gong, Yiran Chen
2111.12170	Domain-Agnostic Clustering with Self-Distillation	Machine Learning (cs.LG)	Mohammed Adnan, Yani A. Ioannou, Chuan-Yung Tsai, Graham W. Taylor
2111.12273	Sharpness-aware Quantization for Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Jing Liu, Jianfei Cai, Bohan Zhuang
2111.12293	PTQ4ViT: Post-Training Quantization Framework for Vision Transformers	Computer Vision and Pattern Recognition (cs.CV)	Zhihang Yuan, Chenhao Xue, Yiqi Chen, Qiang Wu, Guangyu Sun
2111.12341	EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Cross-modal Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Lin Wang, Yujeong Chae, Sung-Hoon Yoon, Tae-Kyun Kim, Kuk-Jin Yoon
2111.12621	Accelerating Deep Learning with Dynamic Data Pruning	Machine Learning (cs.LG)	Ravi S Raju, Kyle Daruwalla, Mikko Lipasti
2111.12958	Self-Distilled Self-Supervised Representation Learning	Computer Vision and Pattern Recognition (cs.CV)	Jiho Jang, Seonhoon Kim, Kiyoon Yoo, Jangho Kim, Nojun Kwak
2111.13112	VaxNeRF: Revisiting the Classic for Voxel-Accelerated Neural Radiance Field	Computer Vision and Pattern Recognition (cs.CV)	Naruya Kondo, Yuya Ikeda, Andrea Tagliasacchi, Yutaka Matsuo, Yoichi Ochiai, Shixiang Shane Gu
2111.13284	Ensembling of Distilled Models from Multi-task Teachers for Constrained Resource Language Pairs	Computation and Language (cs.CL)	Amr Hendy, Esraa A. Gad, Mohamed Abdelghaffar, Jailan S. ElMosalami, Mohamed Afify, Ahmed Y. Tawfik, Hany Hassan Awadalla
2111.13850	Temporal Context Mining for Learned Video Compression	Computer Vision and Pattern Recognition (cs.CV)	Xihua Sheng, Jiahao Li, Bin Li, Li Li, Dong Liu, Yan Lu
2111.13999	Exploring Low-Cost Transformer Model Compression for Large-Scale Commercial Reply Suggestions	Computation and Language (cs.CL)	Vaishnavi Shrivastava, Radhika Gaonkar, Shashank Gupta, Abhishek Jha
2111.14302	Feature-Gate Coupling for Dynamic Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Mengnan Shi, Chang Liu, Qixiang Ye, Jianbin Jiao
2111.14347	Efficient Federated Learning for AIoT Applications Using Knowledge Distillation	Machine Learning (cs.LG)	Tian Liu, Jun Xia, Xian Wei, Ting Wang, Xin Fu, Mingsong Chen
2111.14353	Semi-supervised Domain Adaptation via Sample-to-Sample Self-Distillation	Computer Vision and Pattern Recognition (cs.CV)	Jeongbeen Yoon, Dahyun Kang, Minsu Cho
2111.14356	Improved Knowledge Distillation via Adversarial Collaboration	Computer Vision and Pattern Recognition (cs.CV)	Zhiqiang Liu, Chengkai Huang, Yanxia Liu
2111.14826	Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation	Computer Vision and Pattern Recognition (cs.CV)	Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric Xing, Zhiqiang Shen
2111.14836	Low-bit Quantization of Recurrent Neural Network Language Models Using Alternating Direction Methods of Multipliers	Machine Learning (cs.LG)	Junhao Xu, Xie Chen, Shoukang Hu, Jianwei Yu, Xunying Liu, Helen Meng
2111.15127	A Unified Pruning Framework for Vision Transformers	Computer Vision and Pattern Recognition (cs.CV)	Hao Yu, Jianxin Wu
2111.15179	A Highly Effective Low-Rank Compression of Deep Neural Networks with Modified Beam-Search and Modified Stable Rank	Machine Learning (cs.LG)	Moonjung Eo, Suhyun Kang, Wonjong Rhee
2112.00398	Effective and efficient structure learning with pruning and model averaging strategies	Machine Learning (cs.LG)	Anthony C. Constantinou, Yang Liu, Neville K. Kitson, Kiattikun Chobtham, Zhigao Guo
2112.00459	Information Theoretic Representation Distillation	Computer Vision and Pattern Recognition (cs.CV)	Roy Miles, Adrián López Rodríguez, Krystian Mikolajczyk
2112.00709	GPU-Accelerated Forward-Backward algorithm with Application to Lattice-Free MMI	Distributed, Parallel, and Cluster Computing (cs.DC)	Lucas Ondel, Léa-Marie Lam-Yee-Mui, Martin Kocour, Caio Filippo Corro, Lukáš Burget
2112.00725	Extrapolating from a Single Image to a Thousand Classes using Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yuki M. Asano, Aaqib Saeed
2112.01048	From Consensus to Disagreement: Multi-Teacher Distillation for Semi-Supervised Relation Extraction	Computation and Language (cs.CL)	Wanli Li, Tieyun Qian
2112.01174	Multi-task Self-distillation for Graph-based Semi-Supervised Learning	Machine Learning (cs.LG)	Yating Ren, Junzhong Ji, Lingfeng Niu, Minglong Lei
2112.01405	FedRAD: Federated Robust Adaptive Distillation	Machine Learning (cs.LG)	Stefán Páll Sturluson, Samuel Trew, Luis Muñoz-González, Matei Grama, Jonathan Passerat-Palmbach, Daniel Rueckert, Amir Alansary
2112.01504	Neural Weight Step Video Compression	Computer Vision and Pattern Recognition (cs.CV)	Mikolaj Czerkawski, Javier Cardona, Robert Atkinson, Craig Michie, Ivan Andonovic, Carmine Clemente, Christos Tachtatzis
2112.01528	A Fast Knowledge Distillation Framework for Visual Recognition	Computer Vision and Pattern Recognition (cs.CV)	Zhiqiang Shen, Eric Xing
2112.01849	Cross-modal Knowledge Distillation for Vision-to-Sensor Action Recognition	Multimedia (cs.MM)	Jianyuan Ni, Raunak Sarbajna, Yang Liu, Anne H.H. Ngu, Yan Yan
2112.01944	Towards Low-loss 1-bit Quantization of User-item Representations for Top-K Recommendation	Information Retrieval (cs.IR)	Yankai Chen, Yifei Zhang, Yingxue Zhang, Huifeng Guo, Jingjie Li, Ruiming Tang, Xiuqiang He, Irwin King
2112.02052	TC-GNN: Accelerating Sparse Graph Neural Network Computation Via Dense Tensor Core on GPUs	Machine Learning (cs.LG)	Yuke Wang, Boyuan Feng, Yufei Ding
2112.02291	KDCTime: Knowledge Distillation with Calibration on InceptionTime for Time-series Classification	Machine Learning (cs.LG)	Xueyuan Gong, Yain-Whar Si, Yongqi Tian, Cong Lin, Xinyuan Zhang, Xiaoxiang Liu
2112.02505	Causal Distillation for Language Models	Computation and Language (cs.CL)	Zhengxuan Wu, Atticus Geiger, Josh Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, Noah D. Goodman
2112.02521	Inf-CP: A Reliable Channel Pruning based on Channel Influence	Machine Learning (cs.LG)	Bilan Lai, Haoran Xiang, Furao Shen
2112.02656	Intrinisic Gradient Compression for Federated Learning	Machine Learning (cs.LG)	Luke Melas-Kyriazi, Franklyn Wang
2112.02834	A Generalized Zero-Shot Quantization of Deep Convolutional Neural Networks via Learned Weights Statistics	Computer Vision and Pattern Recognition (cs.CV)	Prasen Kumar Sharma, Arun Abraham, Vikram Nelvoy Rajendiran
2112.03149	Distilled Domain Randomization	Machine Learning (cs.LG)	Julien Brosseit, Benedikt Hahner, Fabio Muratore, Michael Gienger, Jan Peters
2112.03235	Simulation Intelligence: Towards a New Generation of Scientific Methods	Artificial Intelligence (cs.AI)	Alexander Lavin, Hector Zenil, Brooks Paige, David Krakauer, Justin Gottschlich, Tim Mattson, Anima Anandkumar, Sanjay Choudry, Kamil Rocki, Atılım Güneş Baydin, Carina Prunkl, Brooks Paige, Olexandr Isayev, Erik Peterson, Peter L. McMahon, Jakob Macke, Kyle Cranmer, Jiaxin Zhang, Haruko Wainwright, Adi Hanuka, Manuela Veloso, Samuel Assefa, Stephan Zheng, Avi Pfeffer
2112.03383	Graph Neural Networks Accelerated Molecular Dynamics	Machine Learning (cs.LG)	Zijie Li, Kazem Meidani, Prakarsh Yadav, Amir Barati Farimani
2112.03473	Improving Neural Cross-Lingual Summarization via Employing Optimal Transport Distance for Knowledge Distillation	Computation and Language (cs.CL)	Thong Nguyen, Luu Anh Tuan
2112.03690	Low-rank Tensor Decomposition for Compression of Convolutional Neural Networks Using Funnel Regularization	Computer Vision and Pattern Recognition (cs.CV)	Bo-Shiuan Chu, Che-Rung Lee
2112.03732	A coarse space acceleration of deep-DDM	Machine Learning (cs.LG)	Valentin Mercier, Serge Gratton, Pierre Boudier
2112.03814	A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial Images	Computer Vision and Pattern Recognition (cs.CV)	Edoardo Arnaudo, Fabio Cermelli, Antonio Tavera, Claudio Rossi, Barbara Caputo
2112.04002	SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning	Machine Learning (cs.LG)	Yuege Xie, Bobby Shi, Hayden Schaeffer, Rachel Ward
2112.04011	Auxiliary Learning for Self-Supervised Video Representation via Similarity-based Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Amirhossein Dadashzadeh, Alan Whone, Majid Mirmehdi
2112.04023	Accelerating Understanding of Scientific Experiments with End to End Symbolic Regression	Machine Learning (cs.LG)	Nikos Arechiga, Francine Chen, Yan-Ying Chen, Yanxia Zhang, Rumen Iliev, Heishiro Toyoda, Kent Lyons
2112.04174	Boosting Contrastive Learning with Relation Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Kai Zheng, Yuanjiang Wang, Ye Yuan
2112.04840	Knowledge Distillation for Object Detection via Rank Mimicking and Prediction-guided Feature Imitation	Computer Vision and Pattern Recognition (cs.CV)	Gang Li, Xiang Li, Yujie Wang, Shanshan Zhang, Yichao Wu, Ding Liang
2112.04905	i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery	Machine Learning (cs.LG)	Cameron R. Wolfe, Anastasios Kyrillidis
2112.05082	Fast Electromagnetic Validations of Large-Scale Digital Coding Metasurfaces Accelerated by Recurrence Rebuild and Retrieval Method	Signal Processing (eess.SP)	Yu Zhao, Shang Xiang, Long Li
2112.05359	Sketching as a Tool for Understanding and Accelerating Self-attention for Long Sequences	Machine Learning (cs.LG)	Yifan Chen, Qi Zeng, Dilek Hakkani-Tur, Di Jin, Heng Ji, Yun Yang
2112.05493	Network Compression via Central Filter	Machine Learning (cs.LG)	Yuanzhi Duan, Xiaofang Hu, Yue Zhou, Qiang Liu, Shukai Duan
2112.05576	GPU-accelerated image alignment for object detection in industrial applications	Computer Vision and Pattern Recognition (cs.CV)	Trung-Son Le, Chyi-Yeu Lin
2112.05638	DisCo: Effective Knowledge Distillation For Contrastive Learning of Sentence Embeddings	Artificial Intelligence (cs.AI)	Xing Wu, Chaochen Gao, Jue Wang, Liangjun Zang, Zhongyuan Wang, Songlin Hu
2112.05646	Mask-invariant Face Recognition through Template-level Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Marco Huber, Fadi Boutros, Florian Kirchbuchner, Naser Damer
2112.05705	Pruning Pretrained Encoders with a Multitask Objective	Computation and Language (cs.CL)	Patrick Xia, Richard Shin
2112.05929	Server-Side Local Gradient Averaging and Learning Rate Acceleration for Scalable Split Learning	Machine Learning (cs.LG)	Shraman Pal, Mansi Uniyal, Jihong Park, Praneeth Vepakomma, Ramesh Raskar, Mehdi Bennis, Moongu Jeon, Jinho Choi
2112.06013	Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph	Computation and Language (cs.CL)	Tong Zhu, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan, Min Zhang
2112.06044	Achieving Low Complexity Neural Decoders via Iterative Pruning	Machine Learning (cs.LG)	Vikrant Malik, Rohan Ghosh, Mehul Motani
2112.06126	Neural Network Quantization for Efficient Inference: A Survey	Machine Learning (cs.LG)	Olivia Weng
2112.06253	Up to 100$\times$ Faster Data-free Knowledge Distillation	Machine Learning (cs.LG)	Gongfan Fang, Kanya Mo, Xinchao Wang, Jie Song, Shitao Bei, Haofei Zhang, Mingli Song
2112.06502	DGL-GAN: Discriminator Guided Learning for GAN Compression	Computer Vision and Pattern Recognition (cs.CV)	Yuesong Tian, Li Shen, Dacheng Tao, Zhifeng Li, Wei Liu
2112.06540	A Study on Token Pruning for ColBERT	Information Retrieval (cs.IR)	Carlos Lassance, Maroua Maachou, Joohee Park, Stéphane Clinchant
2112.07007	Acceleration techniques for optimization over trained neural network ensembles	Machine Learning (cs.LG)	Keliang Wang, Leonardo Lozano, Carlos Cardonha, David Bergman
2112.07198	From Dense to Sparse: Contrastive Pruning for Better Pre-trained Language Model Compression	Computation and Language (cs.CL)	Runxin Xu, Fuli Luo, Chengyu Wang, Baobao Chang, Jun Huang, Songfang Huang, Fei Huang
2112.07252	A Deep Knowledge Distillation framework for EEG assisted enhancement of single-lead ECG based sleep staging	Signal Processing (eess.SP)	Vaibhav Joshi, Sricharan Vijayarangan, Preejith SP, Mohanasankar Sivaprakasam
2112.07282	SNF: Filter Pruning via Searching the Proper Number of Filters	Computer Vision and Pattern Recognition (cs.CV)	Pengkun Liu, Yaru Yue, Yanjun Guo, Xingxiang Tao, Xiaoguang Zhou
2112.07790	Maximum Bayes Smatch Ensemble Distillation for AMR Parsing	Computation and Language (cs.CL)	Young-Suk Lee, Ramon Fernandez Astudillo, Thanh Lam Hoang, Tahira Naseem, Radu Florian, Salim Roukos
2112.08227	An Experimental Study of the Impact of Pre-training on the Pruning of a Convolutional Neural Network	Computer Vision and Pattern Recognition (cs.CV)	Nathan Hubens, Matei Mancas, Bernard Gosselin, Marius Preda, Titus Zaharia
2112.08655	Feature Distillation Interaction Weighting Network for Lightweight Image Super-Resolution	Computer Vision and Pattern Recognition (cs.CV)	Guangwei Gao, Wenjie Li, Juncheng Li, Fei Wu, Huimin Lu, Yi Yu
2112.08676	Machine Learning-Accelerated Computational Solid Mechanics: Application to Linear Elasticity	Machine Learning (cs.LG)	Rajat Arora
2112.08723	Distilled Dual-Encoder Model for Vision-Language Understanding	Computation and Language (cs.CL)	Zekun Wang, Wenhui Wang, Haichao Zhu, Ming Liu, Bing Qin, Furu Wei
2112.08816	Self-Distilled Hashing for Deep Image Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Young Kyun Jang, Geonmo Gu, Byungsoo Ko, Nam Ik Cho
2112.09355	From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization	Distributed, Parallel, and Cluster Computing (cs.DC)	Feijie Wu, Song Guo, Haozhao Wang, Zhihao Qu, Haobo Zhang, Jie Zhang, Ziming Liu
2112.09445	Data Efficient Language-supervised Zero-shot Recognition with Optimal Transport Distillation	Computer Vision and Pattern Recognition (cs.CV)	Bichen Wu, Ruizhe Cheng, Peizhao Zhang, Peter Vajda, Joseph E. Gonzalez
2112.09448	Distillation of Human-Object Interaction Contexts for Action Recognition	Computer Vision and Pattern Recognition (cs.CV)	Muna Almushyti, Frederick W. Li
2112.09532	Pixel Distillation: A New Knowledge Distillation Scheme for Low-Resolution Image Recognition	Computer Vision and Pattern Recognition (cs.CV)	Guangyu Guo, Longfei Han, Junwei Han, Dingwen Zhang
2112.09655	Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes (Technical Report)	Machine Learning (cs.LG)	Florent Delgrange, Ann Nowé, Guillermo A. Pérez
2112.09786	Distill and De-bias: Mitigating Bias in Face Recognition using Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Prithviraj Dhar, Joshua Gleason, Aniket Roy, Carlos D. Castillo, P. Jonathon Phillips, Rama Chellappa
2112.09891	Equilibrated Zeroth-Order Unrolled Deep Networks for Accelerated MRI	Machine Learning (cs.LG)	Zhuo-Xu Cui, Jing Cheng, Qingyong Zhu, Yuanyuan Liu, Sen Jia, Kankan Zhao, Ziwen Ke, Wenqi Huang, Haifeng Wang, Yanjie Zhu, Dong Liang
2112.09908	Anomaly Discovery in Semantic Segmentation via Distillation Comparison Networks	Computer Vision and Pattern Recognition (cs.CV)	Huan Zhou, Shi Gong, Yu Zhou, Zengqiang Zheng, Ronghua Liu, Xiang Bai
2112.10047	Controlling the Quality of Distillation in Response-Based Network Compression	Computer Vision and Pattern Recognition (cs.CV)	Vibhas Vats, David Crandall
2112.10063	Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Rongrong Ma, Guansong Pang, Ling Chen, Anton van den Hengel
2112.10229	On Causal Inference for Data-free Structured Pruning	Machine Learning (cs.LG)	Martin Ferianc, Anush Sankaran, Olivier Mastropietro, Ehsan Saboori, Quentin Cappart
2112.10408	Efficient Wind Speed Nowcasting with GPU-Accelerated Nearest Neighbors Algorithm	Machine Learning (cs.LG)	Arnaud Pannatier, Ricardo Picatoste, François Fleuret
2112.10769	Logarithmic Unbiased Quantization: Simple 4-bit Training in Deep Learning	Machine Learning (cs.LG)	Brian Chmiel, Ron Banner, Elad Hoffer, Hilla Ben Yaacov, Daniel Soudry
2112.11312	Implicit Neural Video Compression	Machine Learning (cs.LG)	Yunfan Zhang, Ties van Rozendaal, Johann Brehmer, Markus Nagel, Taco Cohen
2112.11438	Mixed Precision Low-bit Quantization of Neural Network Language Models for Speech Recognition	Computation and Language (cs.CL)	Junhao Xu, Jianwei Yu, Shoukang Hu, Xunying Liu, Helen Meng
2112.11447	Multi-Modality Distillation via Learning the teacher's modality-level Gram Matrix	Artificial Intelligence (cs.AI)	Peng Liu
2112.11480	On the Compression of Natural Language Models	Computation and Language (cs.CL)	Saeed Damadi
2112.11540	Mixed Precision of Quantization of Transformer Language Models for Speech Recognition	Computation and Language (cs.CL)	Junhao Xu, Shoukang Hu, Jianwei Yu, Xunying Liu, Helen Meng
2112.11610	EyePAD++: A Distillation-based approach for joint Eye Authentication and Presentation Attack Detection using Periocular Images	Computer Vision and Pattern Recognition (cs.CV)	Prithviraj Dhar, Amit Kumar, Kirsten Kaplan, Khushi Gupta, Rakesh Ranjan, Rama Chellappa
2112.11640	Self-Distillation Mixup Training for Non-autoregressive Neural Machine Translation	Computation and Language (cs.CL)	Jiaxin Guo, Minghan Wang, Daimeng Wei, Hengchao Shang, Yuxia Wang, Zongyao Li, Zhengzhe Yu, Zhanglin Wu, Yimeng Chen, Chang Su, Min Zhang, Lizhi Lei, shimin tao, Hao Yang
2112.11663	Accelerated Proximal Alternating Gradient-Descent-Ascent for Nonconvex Minimax Machine Learning	Machine Learning (cs.LG)	Ziyi Chen, Shaocong Ma, Yi Zhou
2112.11736	An Efficient Pruning Process with Locality Aware Exploration and Dynamic Graph Editing for Subgraph Matching	Information Retrieval (cs.IR)	Zite Jiang, Boxiao Liu, Shuai Zhang, Xingzhong Hou, Mengting Yuan, Haihang You
2112.12635	AcME -- Accelerated Model-agnostic Explanations: Fast Whitening of the Machine-Learning Black Box	Machine Learning (cs.LG)	David Dandolo, Chiara Masiero, Mattia Carletti, Davide Dalle Pezze, Gian Antonio Susto
2112.12650	Distilling the Knowledge of Romanian BERTs Using Multiple Teachers	Computation and Language (cs.CL)	Andrei-Marius Avram, Darius Catrina, Dumitru-Clementin Cercel, Mihai Dascălu, Traian Rebedea, Vasile Păiş, Dan Tufiş
2112.13006	Stochastic Learning Equation using Monotone Increasing Resolution of Quantization	Machine Learning (cs.LG)	Jinwuk Seok, Jeong-Si Kim
2112.13109	Accelerated and instance-optimal policy evaluation with linear function approximation	Machine Learning (stat.ML)	Tianjiao Li, Guanghui Lan, Ashwin Pananjady
2112.13843	BMPQ: Bit-Gradient Sensitivity Driven Mixed-Precision Quantization of DNNs from Scratch	Computer Vision and Pattern Recognition (cs.CV)	Souvik Kundu, Shikai Wang, Qirui Sun, Peter A. Beerel, Massoud Pedram
2112.13890	SPViT: Enabling Faster Vision Transformers via Soft Token Pruning	Computer Vision and Pattern Recognition (cs.CV)	Zhenglun Kong, Peiyan Dong, Xiaolong Ma, Xin Meng, Wei Niu, Mengshu Sun, Bin Ren, Minghai Qin, Hao Tang, Yanzhi Wang
2112.13891	GPU-accelerated Faster Mean Shift with euclidean distance metrics	Computer Vision and Pattern Recognition (cs.CV)	Le You, Han Jiang, Jinyong Hu, Chorng Chang, Lingxi Chen, Xintong Cui, Mengyang Zhao
2112.13953	Source Feature Compression for Object Classification in Vision-Based Underwater Robotics	Computer Vision and Pattern Recognition (cs.CV)	Xueyuan Zhao, Mehdi Rahmati, Dario Pompili
2112.13966	Online Adversarial Distillation for Graph Neural Networks	Machine Learning (cs.LG)	Can Wang, Zhe Wang, Defang Chen, Sheng Zhou, Yan Feng, Chun Chen
2112.14938	Automatic Mixed-Precision Quantization Search of BERT	Computation and Language (cs.CL)	Changsheng Zhao, Ting Hua, Yilin Shen, Qian Lou, Hongxia Jin
2112.15358	Conditional generative data-free knowledge distillation	Computer Vision and Pattern Recognition (cs.CV)	Xinyi Yu, Ling Yan, Yang Yang, Libo Zhou, Linlin Ou
2112.15445	Speedup deep learning models on GPU by taking advantage of efficient unstructured pruning and bit-width reduction	Machine Learning (cs.LG)	Marcin Pietroń, Dominik Żurek
2112.15579	Single-Shot Pruning for Offline Reinforcement Learning	Machine Learning (cs.LG)	Samin Yeasar Arnob, Riyasat Ohib, Sergey Plis, Doina Precup
2201.00007	Confidence-Aware Multi-Teacher Knowledge Distillation	Machine Learning (cs.LG)	Hailin Zhang, Defang Chen, Can Wang
2201.00011	An Efficient Federated Distillation Learning System for Multi-task Time Series Classification	Machine Learning (cs.LG)	Huanlai Xing, Zhiwen Xiao, Rong Qu, Zonghai Zhu, Bowen Zhao
2201.00043	Multi-Dimensional Model Compression of Vision Transformer	Computer Vision and Pattern Recognition (cs.CV)	Zejiang Hou, Sun-Yuan Kung
2201.00111	Role of Data Augmentation Strategies in Knowledge Distillation for Wearable Sensor Data	Machine Learning (cs.LG)	Eun Som Jeon, Anirudh Som, Ankita Shukla, Kristina Hasanaj, Matthew P. Buman, Pavan Turaga
2201.00558	Which Student is Best? A Comprehensive Knowledge Distillation Exam for Task-Specific BERT Models	Computation and Language (cs.CL)	Made Nindyatama Nityasya, Haryo Akbarianto Wibowo, Rendi Chevi, Radityo Eko Prasojo, Alham Fikri Aji
2201.00672	Compression-Resistant Backdoor Attack against Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Mingfu Xue, Xin Wang, Shichang Sun, Yushu Zhang, Jian Wang, Weiqiang Liu
2201.00695	An Efficient Combinatorial Optimization Model Using Learning-to-Rank Distillation	Information Retrieval (cs.IR)	Honguk Woo, Hyunsung Lee, Sangwoo Cho
2201.00701	Scalable semi-supervised dimensionality reduction with GPU-accelerated EmbedSOM	Machine Learning (cs.LG)	Adam Šmelko, Soňa Molnárová, Miroslav Kratochvíl, Abhishek Koladiya, Jan Musil, Martin Kruliš, Jiří Vondrášek
2201.01709	The Effect of Model Compression on Fairness in Facial Expression Recognition	Computer Vision and Pattern Recognition (cs.CV)	Samuil Stoychev, Hatice Gunes
2201.01856	Elastic Product Quantization for Time Series	Machine Learning (cs.LG)	Pieter Robberechts, Wannes Meert, Jesse Davis
2201.02620	Compressing Models with Few Samples: Mimicking then Replacing	Machine Learning (cs.LG)	Huanyu Wang, Junjie Liu, Xin Ma, Yang Yong, Zhenhua Chai, Jianxin Wu
2201.02741	Two-Pass End-to-End ASR Model Compression	Audio and Speech Processing (eess.AS)	Nauman Dawalatabad, Tushar Vatsal, Ashutosh Gupta, Sungsoo Kim, Shatrughan Singh, Dhananjaya Gowda, Chanwoo Kim
2201.03019	Robust and Resource-Efficient Data-Free Knowledge Distillation by Generative Pseudo Replay	Machine Learning (cs.LG)	Kuluhan Binici, Shivam Aggarwal, Nam Trung Pham, Karianto Leman, Tulika Mitra
2201.03169	FedDTG:Federated Data-Free Knowledge Distillation via Three-Player Generative Adversarial Networks	Machine Learning (cs.LG)	Zhenyuan Zhang
2201.03172	Communication-Efficient Federated Learning with Acceleration of Global Momentum	Machine Learning (cs.LG)	Geeho Kim, Jinkyu Kim, Bohyung Han
2201.04042	Towards Lightweight Neural Animation : Exploration of Neural Network Pruning in Mixture of Experts-based Animation Models	Computer Vision and Pattern Recognition (cs.CV)	Antoine Maiorca, Nathan Hubens, Sohaib Laraba, Thierry Dutoit
2201.04131	Optimally compressing VC classes	Machine Learning (cs.LG)	Zachary Chase
2201.04388	OCSampler: Compressing Videos to One Clip with Single-step Sampling	Computer Vision and Pattern Recognition (cs.CV)	Jintao Lin, Haodong Duan, Kai Chen, Dahua Lin, Limin Wang
2201.04440	Accelerated Projected Gradient Method for the Optimization of Cell-Free Massive MIMO Downlink	Signal Processing (eess.SP)	Muhammad Farooq, Hien Quoc Ngo, Le-Nam Tran
2201.04614	SIMD Lossy Compression for Scientific Data	Distributed, Parallel, and Cluster Computing (cs.DC)	Griffin Dube, Jiannan Tian, Sheng Di, Dingwen Tao, Jon Calhoun, Franck Cappello
2201.04813	Recursive Least Squares for Training and Pruning Convolutional Neural Networks	Machine Learning (cs.LG)	Tianzong Yu, Chunyuan Zhang, Yuan Wang, Meng Ma, Qi Song
2201.04913	Compressing Word Embeddings Using Syllables	Computation and Language (cs.CL)	Laurent Mertens, Joost Vennekens
2201.05024	Real-Time GPU-Accelerated Machine Learning Based Multiuser Detection for 5G and Beyond	Signal Processing (eess.SP)	Matthias Mehlhose, Guillermo Marcus, Daniel Schäufele, Daniyal Amir Awan, Nikolaus Binder, Martin Kasparick, Renato L. G. Cavalcante, Sławomir Stańczak, Alexander Keller
2201.05088	Grow-and-Clip: Informative-yet-Concise Evidence Distillation for Answer Explanation	Computation and Language (cs.CL)	Yuyan Chen, Yanghua Xiao, Bang Liu
2201.05131	SimReg: Regression as a Simple Yet Effective Tool for Self-supervised Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	K L Navaneet, Soroush Abbasi Koohpayegani, Ajinkya Tejankar, Hamed Pirsiavash
2201.05540	Compact Graph Structure Learning via Mutual Information Compression	Machine Learning (cs.LG)	Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi
2201.05729	CLIP-TD: CLIP Targeted Distillation for Vision-Language Tasks	Computer Vision and Pattern Recognition (cs.CV)	Zhecan Wang, Noel Codella, Yen-Chun Chen, Luowei Zhou, Jianwei Yang, Xiyang Dai, Bin Xiao, Haoxuan You, Shih-Fu Chang, Lu Yuan
2201.05809	Weighting and Pruning based Ensemble Deep Random Vector Functional Link Network for Tabular Data Classification	Machine Learning (cs.LG)	Qiushi Shi, Ponnuthurai Nagaratnam Suganthan, Rakesh Katuwal
2201.05842	UDC: Unified DNAS for Compressible TinyML Models	Machine Learning (cs.LG)	Igor Fedorov, Ramon Matas, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul Whatmough
2201.06376	UWC: Unit-wise Calibration Towards Rapid Network Compression	Computer Vision and Pattern Recognition (cs.CV)	Chen Lin, Zheyang Li, Bo Peng, Haoji Hu, Wenming Tan, Ye Ren, Shiliang Pu
2201.06378	Self-Supervised Anomaly Detection by Self-Distillation and Negative Sampling	Artificial Intelligence (cs.AI)	Nima Rafiee, Rahil Gholamipoorfard, Nikolas Adaloglou, Simon Jaxy, Julius Ramakers, Markus Kollmann
2201.06459	A Novel Framework to Jointly Compress and Index Remote Sensing Images for Efficient Content-Based Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Jun Xiang, Gencer Sumbul, Nimisha Thekke Madam, Begüm Demir
2201.06507	Distillation from heterogeneous unlabeled collections	Machine Learning (cs.LG)	Jean-Michel Begon, Pierre Geurts
2201.06734	Cross-modal Contrastive Distillation for Instructional Activity Anticipation	Computer Vision and Pattern Recognition (cs.CV)	Zhengyuan Yang, Jingen Liu, Jing Huang, Xiaodong He, Tao Mei, Chenliang Xu, Jiebo Luo
2201.06776	Pruning-aware Sparse Regularization for Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Nanfei Jiang, Xu Zhao, Chaoyang Zhao, Yongqi An, Ming Tang, Jinqiao Wang
2201.06945	It's All in the Head: Representation Knowledge Distillation through Classifier Sharing	Computer Vision and Pattern Recognition (cs.CV)	Emanuel Ben-Baruch, Matan Karklinsky, Yossi Biton, Avi Ben-Cohen, Hussam Lawen, Nadav Zamir
2201.07016	Accelerating Representation Learning with View-Consistent Dynamics in Data-Efficient Reinforcement Learning	Machine Learning (cs.LG)	Tao Huang, Jiachen Wang, Xiao Chen
2201.07428	Variable Augmented Network for Invertible MR Coil Compression	Computer Vision and Pattern Recognition (cs.CV)	Xianghao Liao, Shanshan Wang, Lanlan Tu, Yuhao Wang, Dong Liang, Qiegen Liu
2201.07486	High-fidelity 3D Model Compression based on Key Spheres	Computer Vision and Pattern Recognition (cs.CV)	Yuanzhan Li, Yuqi Liu, Yujie Lu, Siyu Zhang, Shen Cai, Yanting Zhang
2201.07703	Q-ViT: Fully Differentiable Quantization for Vision Transformer	Computer Vision and Pattern Recognition (cs.CV)	Zhexin Li, Tong Yang, Peisong Wang, Jian Cheng
2201.08024	UKD: Debiasing Conversion Rate Estimation via Uncertainty-regularized Knowledge Distillation	Information Retrieval (cs.IR)	Zixuan Xu, Penghui Wei, Weimin Zhang, Shaoguo Liu, Liang Wang, Bo Zheng
2201.08311	Accelerated Gradient Flow: Risk, Stability, and Implicit Regularization	Machine Learning (stat.ML)	Yue Sheng, Alnur Ali
2201.08442	Neural Network Quantization with AI Model Efficiency Toolkit (AIMET)	Machine Learning (cs.LG)	Sangeetha Siddegowda, Marios Fournarakis, Markus Nagel, Tijmen Blankevoort, Chirag Patel, Abhijit Khobare
2201.08542	Can Model Compression Improve NLP Fairness	Computation and Language (cs.CL)	Guangxuan Xu, Qingyuan Hu
2201.08543	Deep Learning-Accelerated 3D Carbon Storage Reservoir Pressure Forecasting Based on Data Assimilation Using Surface Displacement from InSAR	Machine Learning (stat.ML)	Hewei Tang, Pengcheng Fu, Honggeun Jo, Su Jiang, Christopher S. Sherman, François Hamon, Nicholas A. Azzolina, Joseph P. Morris
2201.09118	Optimizing Huffman Decoding for Error-Bounded Lossy Compression on GPUs	Distributed, Parallel, and Cluster Computing (cs.DC)	Cody Rivera, Sheng Di, Jiannan Tian, Xiaodong Yu, Dingwen Tao, Franck Cappello
2201.09441	Federated Unlearning with Knowledge Distillation	Machine Learning (cs.LG)	Chen Wu, Sencun Zhu, Prasenjit Mitra
2201.09483	A Machine Learning Framework for Distributed Functional Compression over Wireless Channels in IoT	Machine Learning (cs.LG)	Yashas Malur Saidutta, Afshin Abdi, Faramarz Fekri
2201.09522	Accelerated Intravascular Ultrasound Imaging using Deep Reinforcement Learning	Signal Processing (eess.SP)	Tristan S.W. Stevens, Nishith Chennakeshava, Frederik J. de Bruijn, Martin Pekař, Ruud J.G. van Sloun
2201.09676	Accelerate Model Parallel Training by Using Efficient Graph Traversal Order in Device Placement	Machine Learning (cs.LG)	Tianze Wang, Amir H. Payberah, Desta Haileselassie Hagos, Vladimir Vlassov
2201.09822	Spectral-PQ: A Novel Spectral Sensitivity-Orientated Perceptual Compression Technique for RGB 4:4:4 Video Data	Computer Vision and Pattern Recognition (cs.CV)	Lee Prangnell, Victor Sanchez
2201.09881	Iterative Activation-based Structured Pruning	Machine Learning (cs.LG)	Kaiqi Zhao, Animesh Jain, Ming Zhao
2201.09884	AutoMC: Automated Model Compression based on Domain Knowledge and Progressive search strategy	Machine Learning (cs.LG)	Chunnan Wang, Hongzhi Wang, Xiangyu Shi
2201.10520	Adaptive Activation-based Structured Pruning	Computer Vision and Pattern Recognition (cs.CV)	Kaiqi Zhao, Animesh Jain, Ming Zhao
2201.10703	Anomaly Detection via Reverse Distillation from One-Class Embedding	Computer Vision and Pattern Recognition (cs.CV)	Hanqiu Deng, Xingyu Li
2201.10830	MonoDistill: Learning Spatial Features for Monocular 3D Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Zhiyu Chong, Xinzhu Ma, Hong Zhang, Yuxin Yue, Haojie Li, Zhihui Wang, Wanli Ouyang
2201.10947	Enabling Deep Learning on Edge Devices through Filter Pruning and Knowledge Transfer	Machine Learning (cs.LG)	Kaiqi Zhao, Yitao Chen, Ming Zhao
2201.11006	An Overview of Compressible and Learnable Image Transformation with Secret Key and Its Applications	Computer Vision and Pattern Recognition (cs.CV)	Hitoshi Kiya, AprilPyone MaungMaung, Yuma Kinoshita, Imaizumi Shoko, Sayaka Shiota
2201.11063	The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity	Neural and Evolutionary Computing (cs.NE)	Christian Pehle, Sebastian Billaudelle, Benjamin Cramer, Jakob Kaiser, Korbinian Schreiber, Yannik Stradmann, Johannes Weis, Aron Leibfried, Eric Müller, Johannes Schemmel
2201.11085	Understanding and Compressing Music with Maximal Transformable Patterns	Machine Learning (cs.LG)	David Meredith
2201.11097	Adaptive Instance Distillation for Object Detection in Autonomous Driving	Computer Vision and Pattern Recognition (cs.CV)	Qizhen Lan, Qing Tian
2201.11103	Auto-Compressing Subset Pruning for Semantic Image Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Konstantin Ditschuneit, Johannes S. Otterbach
2201.11113	Post-training Quantization for Neural Networks with Provable Guarantees	Machine Learning (cs.LG)	Jinjie Zhang, Yixuan Zhou, Rayan Saab
2201.11209	On The Energy Statistics of Feature Maps in Pruning of Neural Networks with Skip-Connections	Machine Learning (cs.LG)	Mohammadreza Soltani, Suya Wu, Yuerong Li, Jie Ding, Vahid Tarokh
2201.11249	Jointly Learning Knowledge Embedding and Neighborhood Consensus with Relational Knowledge Distillation for Entity Alignment	Machine Learning (cs.LG)	Xinhang Li, Yong Zhang, Chunxiao Xing
2201.11319	Dynamic Rectification Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Fahad Rahman Amik, Ahnaf Ismat Tasin, Silvia Ahmed, M. M. Lutfe Elahi, Nabeel Mohammed
2201.11331	Epistemic AI platform accelerates innovation by connecting biomedical knowledge	Artificial Intelligence (cs.AI)	Emily Koo, Heather Bowling, Kenneth Ashworth, David J. Heeger, Stefano Pacifico
2201.11651	Bit-serial Weight Pools: Compression and Arbitrary Precision Execution of Neural Networks on Resource Constrained Processors	Machine Learning (cs.LG)	Shurui Li, Puneet Gupta
2201.11661	TrustAL: Trustworthy Active Learning using Knowledge Distillation	Machine Learning (cs.LG)	Beong-woo Kwak, Youngwook Kim, Yu Jin Kim, Seung-won Hwang, Jinyoung Yeo
2201.11803	On the Convergence of Heterogeneous Federated Learning with Arbitrary Adaptive Online Model Pruning	Machine Learning (cs.LG)	Hanhan Zhou, Tian Lan, Guru Venkataramani, Wenbo Ding
2201.12425	CoordX: Accelerating Implicit Neural Representation with a Split MLP Architecture	Computer Vision and Pattern Recognition (cs.CV)	Ruofan Liang, Hongyi Sun, Nandita Vijaykumar
2201.12469	ScaLA: Accelerating Adaptation of Pre-Trained Transformer-Based Language Models via Efficient Large-Batch Adversarial Noise	Machine Learning (cs.LG)	Minjia Zhang, Niranjan Uma Naresh, Yuxiong He
2201.12507	AutoDistil: Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models	Computation and Language (cs.CL)	Dongkuan Xu, Subhabrata Mukherjee, Xiaodong Liu, Debadeepta Dey, Wenhui Wang, Xiang Zhang, Ahmed Hassan Awadallah, Jianfeng Gao
2201.12592	Exact Decomposition of Joint Low Rankness and Local Smoothness Plus Sparse Matrices	Computer Vision and Pattern Recognition (cs.CV)	Jiangjun Peng, Yao Wang, Hongying Zhang, Jianjun Wang, Deyu Meng
2201.12712	Win the Lottery Ticket via Fourier Analysis: Frequencies Guided Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Yuzhang Shang, Bin Duan, Ziliang Zong, Liqiang Nie, Yan Yan
2201.12904	COIN++: Data Agnostic Neural Compression	Machine Learning (cs.LG)	Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Goliński, Yee Whye Teh, Arnaud Doucet
2201.13096	SPDY: Accurate Pruning with Speedup Guarantees	Machine Learning (cs.LG)	Elias Frantar, Dan Alistarh
2201.13320	BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression	Machine Learning (cs.LG)	Haoyu Zhao, Boyue Li, Zhize Li, Peter Richtárik, Yuejie Chi
2202.00264	Graph-based Neural Acceleration for Nonnegative Matrix Factorization	Machine Learning (cs.LG)	Jens Sjölund, Maria Bånkestad
2202.00512	Progressive Distillation for Fast Sampling of Diffusion Models	Machine Learning (cs.LG)	Tim Salimans, Jonathan Ho
2202.00598	Combined Pruning for Nested Cross-Validation to Accelerate Automated Hyperparameter Optimization for Embedded Feature Selection in High-Dimensional Data with Very Small Sample Sizes	Machine Learning (cs.LG)	Sigrun May, Sven Hartmann, Frank Klawonn
2202.00774	Accelerating DNN Training with Structured Data Gradient Pruning	Machine Learning (cs.LG)	Bradley McDanel, Helia Dinh, John Magallanes
2202.00892	Does Video Compression Impact Tracking Accuracy?	Computer Vision and Pattern Recognition (cs.CV)	Takehiro Tanaka, Alon Harell, Ivan V. Bajić
2202.01118	On Linear Separability under Linear Compression with Applications to Hard Support Vector Machine	Machine Learning (cs.LG)	Paul McVay, Dr. Tie Liu, Dr. Krishna Narayanan
2202.01214	Approximate Bisimulation Relations for Neural Networks and Application to Assured Neural Network Compression	Machine Learning (cs.LG)	Weiming Xiang, Zhongzhu Shao
2202.01258	Accelerated Quality-Diversity for Robotics through Massive Parallelism	Neural and Evolutionary Computing (cs.NE)	Bryan Lim, Maxime Allard, Luca Grillotti, Antoine Cully
2202.01268	DASHA: Distributed Nonconvex Optimization with Communication Compression, Optimal Oracle Complexity, and No Client Synchronization	Machine Learning (cs.LG)	Alexander Tyurin, Peter Richtárik
2202.01290	Cyclical Pruning for Sparse Neural Networks	Machine Learning (cs.LG)	Suraj Srinivas, Andrey Kuzmin, Markus Nagel, Mart van Baalen, Andrii Skliar, Tijmen Blankevoort
2202.01334	Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization	Machine Learning (cs.LG)	Dianbo Liu, Alex Lamb, Xu Ji, Pascal Notsawo, Mike Mozer, Yoshua Bengio, Kenji Kawaguchi
2202.01341	Robust Binary Models by Pruning Randomly-initialized Networks	Machine Learning (cs.LG)	Chen Liu, Ziqi Zhao, Sabine Süsstrunk, Mathieu Salzmann
2202.02265	Iterative Self Knowledge Distillation -- From Pothole Classification to Fine-Grained and COVID Recognition	Computer Vision and Pattern Recognition (cs.CV)	Kuan-Chuan Peng
2202.02643	The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training	Machine Learning (cs.LG)	Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy
2202.02661	LiDAR dataset distillation within bayesian active learning framework: Understanding the effect of data augmentation	Computer Vision and Pattern Recognition (cs.CV)	Ngoc Phuong Anh Duong, Alexandre Almin, Léo Lemarié, B Ravi Kiran
2202.02812	Lossy Gradient Compression: How Much Accuracy Can One Bit Buy?	Machine Learning (cs.LG)	Sadaf Salehkalaibar, Stefano Rini
2202.02971	Locally Differentially Private Distributed Deep Learning via Knowledge Distillation	Machine Learning (cs.LG)	Di Zhuang, Mingchen Li, J. Morris Chang
2202.03068	Artificial Intelligence based tool wear and defect prediction for special purpose milling machinery using low-cost acceleration sensor retrofits	Machine Learning (cs.LG)	Mahmoud Kheir-Eddine, Michael Banf, Gregor Steinhagen
2202.03250	ALM-KD: Knowledge Distillation with noisy labels via adaptive loss mixing	Machine Learning (cs.LG)	Durga Sivasubramanian, Pradeep Shenoy, Prathosh AP, Ganesh Ramakrishnan
2202.03384	Hybrid Contrastive Quantization for Efficient Cross-View Video Retrieval	Information Retrieval (cs.IR)	Jinpeng Wang, Bin Chen, Dongliang Liao, Ziyun Zeng, Gongfu Li, Shu-Tao Xia, Jin Xu
2202.03680	Exploring Inter-Channel Correlation for Diversity-preserved KnowledgeDistillation	Computer Vision and Pattern Recognition (cs.CV)	Li Liu, Qingle Huang, Sihao Lin, Hongwei Xie, Bing Wang, Xiaojun Chang, Xiaodan Liang
2202.03844	EvoPruneDeepTL: An Evolutionary Pruning Model for Transfer Learning based Deep Neural Networks	Neural and Evolutionary Computing (cs.NE)	Javier Poyatos, Daniel Molina, Aritz. D. Martinez, Javier Del Ser, Francisco Herrera
2202.04241	Distillation with Contrast is All You Need for Self-Supervised Point Cloud Representation Learning	Computer Vision and Pattern Recognition (cs.CV)	Kexue Fu, Peng Gao, Renrui Zhang, Hongsheng Li, Yu Qiao, Manning Wang
2202.04822	Survey on Graph Neural Network Acceleration: An Algorithmic Perspective	Machine Learning (cs.LG)	Xin Liu, Mingyu Yan, Lei Deng, Guoqi Li, Xiaochun Ye, Dongrui Fan, Shirui Pan, Yuan Xie
2202.04876	Distilling Hypernymy Relations from Language Models: On the Effectiveness of Zero-Shot Taxonomy Induction	Computation and Language (cs.CL)	Devansh Jain, Luis Espinosa Anke
2202.04954	D2A-BSP: Distilled Data Association Belief Space Planning with Performance Guarantees Under Budget Constraints	Artificial Intelligence (cs.AI)	Moshe Shienman, Vadim Indelman
2202.05048	Quantune: Post-training Quantization of Convolutional Neural Networks using Extreme Gradient Boosting for Fast Deployment	Machine Learning (cs.LG)	Jemin Lee, Misun Yu, Yongin Kwon, Taeho Kim
2202.05137	Quantization in Layer's Input is Matter	Machine Learning (cs.LG)	Daning Cheng, WenGuang Chen
2202.05226	Deadwooding: Robust Global Pruning for Deep Neural Networks	Machine Learning (cs.LG)	Sawinder Kaur, Ferdinando Fioretto, Asif Salekin (Syracuse University, USA)
2202.05239	F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization	Computer Vision and Pattern Recognition (cs.CV)	Qing Jin, Jian Ren, Richard Zhuang, Sumant Hanumante, Zhengang Li, Zhiyu Chen, Yanzhi Wang, Kaiyuan Yang, Sergey Tulyakov
2202.06580	Improved Aggregating and Accelerating Training Methods for Spatial Graph Neural Networks on Fraud Detection	Machine Learning (cs.LG)	Yufan Zeng, Jiashan Tang
2202.07105	A Survey on Model Compression for Natural Language Processing	Computation and Language (cs.CL)	Canwen Xu, Julian McAuley
2202.07190	Pruning Networks with Cross-Layer Ranking & k-Reciprocal Nearest Filters	Computer Vision and Pattern Recognition (cs.CV)	Mingbao Lin, Liujuan Cao, Yuxin Zhang, Ling Shao, Chia-Wen Lin, Rongrong Ji
2202.07191	Improving Human Sperm Head Morphology Classification with Unsupervised Anatomical Feature Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yejia Zhang, Jingjing Zhang, Xiaomin Zha, Yiru Zhou, Yunxia Cao, Danny Chen
2202.07244	Explaining Reject Options of Learning Vector Quantization Classifiers	Machine Learning (cs.LG)	André Artelt, Johannes Brinkrolf, Roel Visser, Barbara Hammer
2202.07258	Accelerating Non-Negative and Bounded-Variable Linear Regression Algorithms with Safe Screening	Machine Learning (cs.LG)	Cassio Dantas (IMAG, UM), Emmanuel Soubies (IRIT-SC, CNRS), Cédric Févotte (IRIT-SC, CNRS)
2202.07268	Convolutional Network Fabric Pruning With Label Noise	Machine Learning (cs.LG)	Ilias Benjelloun (SYNALP), Bart Lamiroy (CRESTIC, SYNALP), Efoevi Koudou (IECL)
2202.07462	Vau da muntanialas: Energy-efficient multi-die scalable acceleration of RNN inference	Machine Learning (cs.LG)	Gianna Paulin, Francesco Conti, Lukas Cavigelli, Luca Benini
2202.07471	SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation	Machine Learning (cs.LG)	Cong Guo, Yuxian Qiu, Jingwen Leng, Xiaotian Gao, Chen Zhang, Yunxin Liu, Fan Yang, Yuhao Zhu, Minyi Guo
2202.07846	Deeply-Supervised Knowledge Distillation	Machine Learning (cs.LG)	Shiya Luo, Defang Chen, Can Wang
2202.07861	Practical Network Acceleration with Tiny Sets	Computer Vision and Pattern Recognition (cs.CV)	Guo-Hua Wang, Jianxin Wu
2202.07940	Meta Knowledge Distillation	Machine Learning (cs.LG)	Jihao Liu, Boxiao Liu, Hongsheng Li, Yu Liu
2202.08132	Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients	Machine Learning (cs.LG)	Milad Alizadeh, Shyam A. Tailor, Luisa M Zintgraf, Joost van Amersfoort, Sebastian Farquhar, Nicholas Donald Lane, Yarin Gal
2202.09009	LG-LSQ: Learned Gradient Linear Symmetric Quantization	Computer Vision and Pattern Recognition (cs.CV)	Shih-Ting Lin, Zhaofang Li, Yu-Hsiang Cheng, Hao-Wen Kuo, Chih-Cheng Lu, Kea-Tiong Tang
2202.09357	ProxSkip: Yes! Local Gradient Steps Provably Lead to Communication Acceleration! Finally!	Machine Learning (cs.LG)	Konstantin Mishchenko, Grigory Malinovsky, Sebastian Stich, Peter Richtárik
2202.09852	Cross-Task Knowledge Distillation in Multi-Task Recommendation	Information Retrieval (cs.IR)	Chenxiao Yang, Junwei Pan, Xiaofeng Gao, Tingyu Jiang, Dapeng Liu, Guihai Chen
2202.10232	Efficient Cross-Modal Retrieval via Deep Binary Hashing and Quantization	Information Retrieval (cs.IR)	Yang Shi, Young-joo Chung
2202.10304	Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion	Computer Vision and Pattern Recognition (cs.CV)	Minghui Liao, Zhisheng Zou, Zhaoyi Wan, Cong Yao, Xiang Bai
2202.10461	A Novel Architecture Slimming Method for Network Pruning and Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Dongqi Wang, Shengyu Zhang, Zhipeng Di, Xin Lin, Weihua Zhou, Fei Wu
2202.10522	Non-Volatile Memory Accelerated Posterior Estimation	Machine Learning (cs.LG)	Andrew Wood, Moshik Hershcovitch, Daniel Waddington, Sarel Cohen, Peter Chin
2202.10584	DeepSketch: A New Machine Learning-Based Reference Search Technique for Post-Deduplication Delta Compression	Machine Learning (cs.LG)	Jisung Park, Jeoggyun Kim, Yeseong Kim, Sungjin Lee, Onur Mutlu
2202.10716	HRel: Filter Pruning based on High Relevance between Activation Maps and Class Labels	Computer Vision and Pattern Recognition (cs.CV)	CH Sarvani, Mrinmoy Ghorai, Shiv Ram Dubey, SH Shabbeer Basha
2202.10728	Distilled Neural Networks for Efficient Learning to Rank	Machine Learning (cs.LG)	F.M. Nardini, C. Rulli, S. Trani, R.Venturini
2202.10742	Acceleration of Gossip Algorithms through the Euler-Poisson-Darboux Equation	Distributed, Parallel, and Cluster Computing (cs.DC)	Raphaël Berthier (SIERRA), Mufan Li
2202.11079	Reward-Free Policy Space Compression for Reinforcement Learning	Machine Learning (cs.LG)	Mirco Mutti, Stefano Del Col, Marcello Restelli
2202.11384	Multi-Teacher Knowledge Distillation for Incremental Implicitly-Refined Classification	Computer Vision and Pattern Recognition (cs.CV)	Longhui Yu, Zhenyu Weng, Yuqing Wang, Yuesheng Zhu
2202.11453	Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization	Machine Learning (cs.LG)	Jaehong Yoon, Geon Park, Wonyong Jeong, Sung Ju Hwang
2202.11518	Non-Volatile Memory Accelerated Geometric Multi-Scale Resolution Analysis	Machine Learning (cs.LG)	Andrew Wood, Moshik Hershcovitch, Daniel Waddington, Sarel Cohen, Meredith Wolf, Hongjun Suh, Weiyu Zong, Peter Chin
2202.11782	Prune and Tune Ensembles: Low-Cost Ensemble Learning With Sparse Independent Subnetworks	Machine Learning (cs.LG)	Tim Whitaker, Darrell Whitley
2202.11836	Sky Computing: Accelerating Geo-distributed Computing in Federated Learning	Machine Learning (cs.LG)	Jie Zhu, Shenggui Li, Yang You
2202.12211	Self-Distilled StyleGAN: Towards Generation from Internet Photos	Computer Vision and Pattern Recognition (cs.CV)	Ron Mokady, Michal Yarom, Omer Tov, Oran Lang, Daniel Cohen-Or, Tali Dekel, Michal Irani, Inbar Mosseri
2202.12400	The rise of the lottery heroes: why zero-shot pruning is hard	Machine Learning (cs.LG)	Enzo Tartaglione
2202.12422	Standard Deviation-Based Quantization for Deep Neural Networks	Machine Learning (cs.LG)	Amir Ardakani, Arash Ardakani, Brett Meyer, James J. Clark, Warren J. Gross
2202.12429	BagPipe: Accelerating Deep Recommendation Model Training	Distributed, Parallel, and Cluster Computing (cs.DC)	Saurabh Agarwal, Ziyi Zhang, Shivaram Venkataraman
2202.12477	HipBone: A performance-portable GPU-accelerated C++ version of the NekBone benchmark	Distributed, Parallel, and Cluster Computing (cs.DC)	Noel Chalmers, Abhishek Mishra, Damon McDougall, Tim Warburton
2202.12488	Learn From the Past: Experience Ensemble Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Chaofei Wang, Shaowei Zhang, Shiji Song, Gao Huang
2202.12598	Bridging the Gap Between Patient-specific and Patient-independent Seizure Prediction via Knowledge Distillation	Machine Learning (cs.LG)	Di Wu, Jie Yang, Mohamad Sawan
2202.12674	PLSSVM: A (multi-)GPGPU-accelerated Least Squares Support Vector Machine	Machine Learning (cs.LG)	Alexander Van Craen, Marcel Breyer, Dirk Pflüger
2202.12934	Accelerating Neural Architecture Exploration Across Modalities Using Genetic Algorithms	Neural and Evolutionary Computing (cs.NE)	Daniel Cummings, Sharath Nittur Sridhar, Anthony Sarah, Maciej Szankin
2202.12943	Arrhythmia Classifier Using Convolutional Neural Network with Adaptive Loss-aware Multi-bit Networks Quantization	Signal Processing (eess.SP)	Hanshi Sun, Ao Wang, Ninghao Pu, Zhiqing Li, Junguang Huang, Hao Liu, Zhi Qi
2202.13123	Content-Variant Reference Image Quality Assessment via Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Guanghao Yin, Wei Wang, Zehuan Yuan, Chuchu Han, Wei Ji, Shouqian Sun, Changhu Wang
2202.13157	High Dimensional Statistical Estimation under One-bit Quantization	Machine Learning (stat.ML)	Junren Chen, Cheng-Long Wang, Michael K. Ng, Di Wang
2202.13393	Transformer-based Knowledge Distillation for Efficient Semantic Segmentation of Road-driving Scenes	Computer Vision and Pattern Recognition (cs.CV)	Ruiping Liu, Kailun Yang, Huayao Liu, Jiaming Zhang, Kunyu Peng, Rainer Stiefelhagen
2202.13590	LCP-dropout: Compression-based Multiple Subword Segmentation for Neural Machine Translation	Computation and Language (cs.CL)	Keita Nonaka, Kazutaka Yamanouchi, Tomohiro I, Tsuyoshi Okita, Kazutaka Shimada, Hiroshi Sakamoto
2202.13654	Cross-Lingual Text Classification with Multilingual Distillation and Zero-Shot-Aware Training	Computation and Language (cs.CL)	Ziqing Yang, Yiming Cui, Zhigang Chen, Shijin Wang
2202.13862	Variable Rate Compression for Raw 3D Point Clouds	Computer Vision and Pattern Recognition (cs.CV)	Md Ahmed Al Muzaddid, William J. Beksi
2203.00236	TRILLsson: Distilled Universal Paralinguistic Speech Representations	Audio and Speech Processing (eess.AS)	Joel Shor, Subhashini Venugopalan
2203.00281	Fast-R2D2: A Pretrained Recursive Neural Network based on Pruned CKY for Grammar Induction and Text Representation	Computation and Language (cs.CL)	Xiang Hu, Haitao Mi, Liang Li, Gerard de Melo
2203.00517	Multi-task Learning Approach for Modulation and Wireless Signal Classification for 5G and Beyond: Edge Deployment via Model Compression	Signal Processing (eess.SP)	Anu Jagannath, Jithin Jagannath
2203.00813	An Accelerated Stochastic Algorithm for Solving the Optimal Transport Problem	Machine Learning (stat.ML)	Yiling Xie, Yiling Luo, Xiaoming Huo
2203.00822	Keeping Minimal Experience to Achieve Efficient Interpretable Policy Distillation	Machine Learning (cs.LG)	Xiao Liu, Shuyang Liu, Wenbin Li, Shangdong Yang, Yang Gao
2203.00862	SEA: Bridging the Gap Between One- and Two-stage Detector Distillation via SEmantic-aware Alignment	Computer Vision and Pattern Recognition (cs.CV)	Yixin Chen, Zhuotao Tian, Pengguang Chen, Shu Liu, Jiaya Jia
2203.01305	DN-DETR: Accelerate DETR Training by Introducing Query DeNoising	Computer Vision and Pattern Recognition (cs.CV)	Feng Li, Hao Zhang, Shilong Liu, Jian Guo, Lionel M. Ni, Lei Zhang
2203.01744	Accelerated SGD for Non-Strongly-Convex Least Squares	Machine Learning (cs.LG)	Aditya Varre, Nicolas Flammarion
2203.01941	Autoregressive Image Generation using Residual Quantization	Computer Vision and Pattern Recognition (cs.CV)	Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, Wook-Shin Han
2203.02096	Portability for GPU-accelerated molecular docking applications for cloud and HPC: can portable compiler directives provide performance across all platforms?	Distributed, Parallel, and Cluster Computing (cs.DC)	Mathialakan Thavappiragasam, Wael Elwasif, Ada Sedova
2203.02250	Patch Similarity Aware Data-Free Quantization for Vision Transformers	Computer Vision and Pattern Recognition (cs.CV)	Zhikai Li, Liping Ma, Mengjuan Chen, Junrui Xiao, Qingyi Gu
2203.02505	ARM 4-BIT PQ: SIMD-based Acceleration for Approximate Nearest Neighbor Search on ARM	Machine Learning (cs.LG)	Yusuke Matsui, Yoshiki Imaizumi, Naoya Miyamoto, Naoki Yoshifuji
2203.02506	Non-linear predictive vector quantization of speech	Machine Learning (cs.LG)	Marcos Faundez-Zanuy
2203.02549	Structured Pruning is All You Need for Pruning CNNs at Initialization	Computer Vision and Pattern Recognition (cs.CV)	Yaohui Cai, Weizhe Hua, Hongzheng Chen, G. Edward Suh, Christopher De Sa, Zhiru Zhang
2203.02645	Acceleration of Federated Learning with Alleviated Forgetting in Local Training	Machine Learning (cs.LG)	Chencheng Xu, Zhiwei Hong, Minlie Huang, Tao Jiang
2203.02651	Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter Pruning	Machine Learning (cs.LG)	Seunghyun Lee, Byung Cheol Song
2203.03137	MSDN: Mutually Semantic Distillation Network for Zero-Shot Learning	Computer Vision and Pattern Recognition (cs.CV)	Shiming Chen, Ziming Hong, Guo-Sen Xie, Wenhan Wang, Qinmu Peng, Kai Wang, Jian Zhao, Xinge You
2203.03218	Enhance Language Identification using Dual-mode Model with Knowledge Distillation	Audio and Speech Processing (eess.AS)	Hexin Liu, Leibny Paola Garcia Perera, Andy W.H. Khong, Justin Dauwels, Suzy J. Styles, Sanjeev Khudanpur
2203.03692	Low-Loss Subspace Compression for Clean Gains against Multi-Agent Backdoor Attacks	Machine Learning (cs.LG)	Siddhartha Datta, Nigel Shadbolt
2203.04076	Semantic Distillation Guided Salient Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Bo Xu, Guanze Liu, Han Huang, Cheng Lu, Yandong Guo
2203.04279	Probabilistic Warp Consistency for Weakly-Supervised Semantic Correspondences	Computer Vision and Pattern Recognition (cs.CV)	Prune Truong, Martin Danelljan, Fisher Yu, Luc Van Gool
2203.04297	Rényi State Entropy for Exploration Acceleration in Reinforcement Learning	Machine Learning (cs.LG)	Mingqi Yuan, Man-on Pun, Dong Wang
2203.04409	A machine learning accelerated inverse design of underwater acoustic polyurethane coatings with cylindrical voids	Signal Processing (eess.SP)	Hansani Weeratunge, Zakiya Shireen, Sagar Iyer, Richard Sandberg, Saman Halgamuge, Adrian Menzel, Andrew Phillips, Elnaz Hajizadeh
2203.04415	Practical cognitive speech compression	Audio and Speech Processing (eess.AS)	Reza Lotfidereshgi, Philippe Gournay
2203.04455	Pruning Graph Convolutional Networks to select meaningful graph frequencies for fMRI decoding	Machine Learning (cs.LG)	Yassine El Ouahidi, Hugo Tessier, Giulia Lioi, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon
2203.04466	The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks	Machine Learning (cs.LG)	Xin Yu, Thiago Serra, Srikumar Ramalingam, Shandian Zhe
2203.04516	Update Compression for Deep Neural Networks on the Edge	Computer Vision and Pattern Recognition (cs.CV)	Bo Chen, Ali Bakhshi, Gustavo Batista, Brian Ng, Tat-Jun Chin
2203.04570	CP-ViT: Cascade Vision Transformer Pruning via Progressive Sparsity Prediction	Computer Vision and Pattern Recognition (cs.CV)	Zhuoran Song, Yihong Xu, Zhezhi He, Li Jiang, Naifeng Jing, Xiaoyao Liang
2203.04635	PRINCE: A Pruned AMP Integrated Deep CNN Method for Efficient Channel Estimation of Millimeter-wave and Terahertz Ultra-Massive MIMO Systems	Signal Processing (eess.SP)	Zhengdong Hu, Yuhang Chen, Chong Han
2203.04781	How many Observations are Enough? Knowledge Distillation for Trajectory Forecasting	Computer Vision and Pattern Recognition (cs.CV)	Alessio Monti, Angelo Porrello, Simone Calderara, Pasquale Coscia, Lamberto Ballan, Rita Cucchiara
2203.04825	Efficient Sub-structured Knowledge Distillation	Machine Learning (cs.LG)	Wenye Lin, Yangming Li, Lemao Liu, Shuming Shi, Hai-tao Zheng
2203.04925	Correlated quantization for distributed mean estimation and optimization	Machine Learning (cs.LG)	Ananda Theertha Suresh, Ziteng Sun, Jae Hun Ro, Felix Yu
2203.04940	Data-Efficient Structured Pruning via Submodular Optimization	Machine Learning (cs.LG)	Marwa El Halabi, Suraj Srinivas, Simon Lacoste-Julien
2203.05016	Shfl-BW: Accelerating Deep Neural Network Inference with Tensor-Core Aware Weight Pruning	Distributed, Parallel, and Cluster Computing (cs.DC)	Guyue Huang, Haoran Li, Minghai Qin, Fei Sun, Yufei Ding, Yuan Xie
2203.05103	Improving Neural ODEs via Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Haoyu Chu, Shikui Wei, Qiming Lu, Yao Zhao
2203.05180	Knowledge Distillation as Efficient Pre-training: Faster Convergence, Higher Data-efficiency, and Better Transferability	Computer Vision and Pattern Recognition (cs.CV)	Ruifei He, Shuyang Sun, Jihan Yang, Song Bai, Xiaojuan Qi
2203.05201	Online Deep Metric Learning via Mutual Distillation	Computer Vision and Pattern Recognition (cs.CV)	Gao-Dong Liu, Wan-Lei Zhao, Jie Zhao
2203.05212	Membership Privacy Protection for Image Translation Models via Adversarial Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Saeed Ranjbar Alvar, Lanjun Wang, Jian Pei, Yong Zhang
2203.05248	Look Backward and Forward: Self-Knowledge Distillation with Bidirectional Decoder for Neural Machine Translation	Computation and Language (cs.CL)	Xuanwei Zhang, Libin Shen, Disheng Pan, Liang Wang, Yanjun Miao
2203.05468	CoCo-FL: Communication- and Computation-Aware Federated Learning via Partial NN Freezing and Quantization	Machine Learning (cs.LG)	Kilian Pfeiffer, Martin Rapp, Ramin Khalili, Jörg Henkel
2203.05469	Prediction-Guided Distillation for Dense Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Chenhongyi Yang, Mateusz Ochal, Amos Storkey, Elliot J. Crowley
2203.05492	An Empirical Study of Low Precision Quantization for TinyML	Machine Learning (cs.LG)	Shaojie Zhuo, Hongyu Chen, Ramchalam Kinattinkara Ramakrishnan, Tommy Chen, Chen Feng, Yicheng Lin, Parker Zhang, Liang Shen
2203.05705	DNN Training Acceleration via Exploring GPGPU Friendly Sparsity	Machine Learning (cs.LG)	Zhuoran Song, Yihong Xu, Han Li, Naifeng Jing, Xiaoyao Liang, Li Jiang
2203.05740	QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization	Computer Vision and Pattern Recognition (cs.CV)	Xiuying Wei, Ruihao Gong, Yuhang Li, Xianglong Liu, Fengwei Yu
2203.05807	Improve Convolutional Neural Network Pruning by Maximizing Filter Variety	Computer Vision and Pattern Recognition (cs.CV)	Nathan Hubens, Matei Mancas, Bernard Gosselin, Marius Preda, Titus Zaharia
2203.06117	GATSPI: GPU Accelerated Gate-Level Simulation for Power Improvement	Machine Learning (cs.LG)	Yanqing Zhang, Haoxing Ren, Akshay Sridharan, Brucek Khailany
2203.06321	Wavelet Knowledge Distillation: Towards Efficient Image-to-Image Translation	Computer Vision and Pattern Recognition (cs.CV)	Linfeng Zhang, Xin Chen, Xiaobing Tu, Pengfei Wan, Ning Xu, Kaisheng Ma
2203.06386	Enabling Multimodal Generation on CLIP via Vision-Language Knowledge Distillation	Computation and Language (cs.CL)	Wenliang Dai, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Pascale Fung
2203.06551	CEKD:Cross Ensemble Knowledge Distillation for Augmented Fine-grained Data	Computer Vision and Pattern Recognition (cs.CV)	Ke Zhang, Jin Fan, Shaoli Huang, Yongliang Qiao, Xiaofeng Yu, Feiwei Qin
2203.06778	Pruned Graph Neural Network for Short Story Ordering	Computation and Language (cs.CL)	Melika Golestani, Zeinab Borhanifard, Farnaz Tahmasebian, Heshaam Faili
2203.06883	Accelerating DETR Convergence via Semantic-Aligned Matching	Computer Vision and Pattern Recognition (cs.CV)	Gongjie Zhang, Zhipeng Luo, Yingchen Yu, Kaiwen Cui, Shijian Lu
2203.06900	Communication-Efficient Federated Distillation with Active Data Sampling	Machine Learning (cs.LG)	Lumin Liu, Jun Zhang, S. H. Song, Khaled B. Letaief
2203.07033	Compressing CNN Kernels for Videos Using Tucker Decompositions: Towards Lightweight CNN Applications	Machine Learning (cs.LG)	Tobias Engelhardt Rasmussen, Line H Clemmensen, Andreas Baum
2203.07159	On the benefits of knowledge distillation for adversarial robustness	Machine Learning (cs.LG)	Javier Maroto, Guillermo Ortiz-Jiménez, Pascal Frossard
2203.07259	The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models	Computation and Language (cs.CL)	Eldar Kurtic, Daniel Campos, Tuan Nguyen, Elias Frantar, Mark Kurtz, Benjamin Fineran, Michael Goin, Dan Alistarh
2203.07585	Accelerating Stochastic Probabilistic Inference	Machine Learning (cs.LG)	Minta Liu, Suliang Bu
2203.07687	Compressing Sentence Representation for Semantic Retrieval via Homomorphic Projective Distillation	Computation and Language (cs.CL)	Xuandong Zhao, Zhiguo Yu, Ming Wu, Lei Li
2203.07808	Interspace Pruning: Using Adaptive Filter Representations to Improve Training of Sparse CNNs	Computer Vision and Pattern Recognition (cs.CV)	Paul Wimmer, Jens Mehnert, Alexandru Paul Condurache
2203.08080	Implicit Feature Decoupling with Depthwise Quantization	Computer Vision and Pattern Recognition (cs.CV)	Iordanis Fostiropoulos, Barry Boehm
2203.08134	Privacy-Aware Compression for Federated Data Analysis	Machine Learning (cs.LG)	Kamalika Chaudhuri, Chuan Guo, Mike Rabbat
2203.08243	Unified Visual Transformer Compression	Machine Learning (cs.LG)	Shixing Yu, Tianlong Chen, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Liu, Zhangyang Wang
2203.08295	Self-Distribution Distillation: Efficient Uncertainty Estimation	Machine Learning (cs.LG)	Yassir Fathullah, Mark J. F. Gales
2203.08368	Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance	Machine Learning (cs.LG)	Chen Tang, Kai Ouyang, Zhi Wang, Yifei Zhu, Yaowei Wang, Wen Ji, Wenwu Zhu
2203.08414	Unsupervised Semantic Segmentation by Distilling Feature Correspondences	Computer Vision and Pattern Recognition (cs.CV)	Mark Hamilton, Zhoutong Zhang, Bharath Hariharan, Noah Snavely, William T. Freeman
2203.08456	PPCD-GAN: Progressive Pruning and Class-Aware Distillation for Large-Scale Conditional GANs Compression	Computer Vision and Pattern Recognition (cs.CV)	Duc Minh Vo, Akihiro Sugimoto, Hideki Nakayama
2203.08667	Graph Flow: Cross-layer Graph Flow Distillation for Dual Efficient Medical Image Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Wenxuan Zou, Muyi Sun
2203.08679	Decoupled Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Borui Zhao, Quan Cui, Renjie Song, Yiyu Qiu, Jiajun Liang
2203.08680	GPU-Accelerated Parallel Gene-pool Optimal Mixing in a Gray-Box Optimization Setting	Neural and Evolutionary Computing (cs.NE)	Anton Bouter, Peter A.N. Bosman
2203.08875	SC2: Supervised Compression for Split Computing	Machine Learning (cs.LG)	Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
2203.09044	Convert, compress, correct: Three steps toward communication-efficient DNN training	Machine Learning (cs.LG)	Zhong-Jing Chen, Eduin E. Hernandez, Yu-Chih Huang, Stefano Rini
2203.09208	Neural Compression-Based Feature Learning for Video Restoration	Computer Vision and Pattern Recognition (cs.CV)	Cong Huang, Jiahao Li, Bin Li, Dong Liu, Yan Lu
2203.09249	Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning	Machine Learning (cs.LG)	Lin Zhang, Li Shen, Liang Ding, Dacheng Tao, Ling-Yu Duan
2203.09430	Mutual Learning for Domain Adaptation: Self-distillation Image Dehazing Network with Sample-cycle	Computer Vision and Pattern Recognition (cs.CV)	Tian Ye, Yun Liu, Yunchen Zhang, Sixiang Chen, Erkang Chen
2203.09487	Defending Against Adversarial Attack in ECG Classification with Adversarial Distillation Training	Signal Processing (eess.SP)	Jiahao Shao, Shijia Geng, Zhaoji Fu, Weilun Xu, Tong Liu, Shenda Hong
2203.09518	Privacy-Preserving Speech Representation Learning using Vector Quantization	Audio and Speech Processing (eess.AS)	Pierre Champion (MULTISPEECH), Denis Jouvet (MULTISPEECH), Anthony Larcher (LIUM)
2203.09594	Delta Distillation for Efficient Video Processing	Computer Vision and Pattern Recognition (cs.CV)	Amirhossein Habibian, Haitam Ben Yahia, Davide Abati, Efstratios Gavves, Fatih Porikli
2203.09737	Semi-Supervised Learning with Mutual Distillation for Monocular Depth Estimation	Computer Vision and Pattern Recognition (cs.CV)	Jongbeom Baek, Gyeongnyeon Kim, Seungryong Kim
2203.09756	AutoAdversary: A Pixel Pruning Method for Sparse Adversarial Attack	Computer Vision and Pattern Recognition (cs.CV)	Jinqiao Li, Xiaotao Liu, Jian Zhao, Furao Shen
2203.09931	3DAC: Learning Attribute Compression for Point Clouds	Computer Vision and Pattern Recognition (cs.CV)	Guangchi Fang, Qingyong Hu, Hanyun Wang, Yiling Xu, Yulan Guo
2203.10006	Ultra-low Latency Spiking Neural Networks with Spatio-Temporal Compression and Synaptic Convolutional Block	Neural and Evolutionary Computing (cs.NE)	Changqing Xu, Yi Liu, Yintang Yang
2203.10065	Symbol quantization in interstellar communications: methods and observations	Signal Processing (eess.SP)	William J. Crilly Jr
2203.10163	A Closer Look at Knowledge Distillation with Features, Logits, and Gradients	Machine Learning (cs.LG)	Yen-Chang Hsu, James Smith, Yilin Shen, Zsolt Kira, Hongxia Jin
2203.10183	Adversarial Attacks on Deep Learning-based Video Compression and Classification Systems	Computer Vision and Pattern Recognition (cs.CV)	Jung-Woo Chang, Mojan Javaheripi, Seira Hidano, Farinaz Koushanfar
2203.10297	Incremental Few-Shot Learning via Implanting and Compressing	Computer Vision and Pattern Recognition (cs.CV)	Yiting Li, Haiyue Zhu, Xijia Feng, Zilong Cheng, Jun Ma, Cheng Xiang, Prahlad Vadakkepat, Tong Heng Lee
2203.10593	Open-Vocabulary One-Stage Detection with Hierarchical Visual-Language Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Zongyang Ma, Guan Luo, Jin Gao, Liang Li, Yuxin Chen, Shaoru Wang, Congxuan Zhang, Weiming Hu
2203.10705	Compression of Generative Pre-trained Language Models via Quantization	Computation and Language (cs.CL)	Chaofan Tao, Lu Hou, Wei Zhang, Lifeng Shang, Xin Jiang, Qun Liu, Ping Luo, Ngai Wong
2203.10900	Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation	Computation and Language (cs.CL)	Qingyu Tan, Ruidan He, Lidong Bing, Hwee Tou Ng
2203.11081	Image Classification on Accelerated Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Ilkay Sikdokur, Inci Baytas, Arda Yurdakul
2203.11086	Overcoming Oscillations in Quantization-Aware Training	Machine Learning (cs.LG)	Markus Nagel, Marios Fournarakis, Yelysei Bondarenko, Tijmen Blankevoort
2203.11160	Drive&Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-modal Distillation	Computer Vision and Pattern Recognition (cs.CV)	Antonin Vobecky, David Hurych, Oriane Siméoni, Spyros Gidaris, Andrei Bursuc, Patrick Pérez, Josef Sivic
2203.11197	Teachable Reinforcement Learning via Advice Distillation	Machine Learning (cs.LG)	Olivia Watkins, Trevor Darrell, Pieter Abbeel, Jacob Andreas, Abhishek Gupta
2203.11239	DQ-BART: Efficient Sequence-to-Sequence Model via Joint Distillation and Quantization	Computation and Language (cs.CL)	Zheng Li, Zijian Wang, Ming Tan, Ramesh Nallapati, Parminder Bhatia, Andrew Arnold, Bing Xiang, Dan Roth
2203.11490	SSD-KD: A Self-supervised Diverse Knowledge Distillation Method for Lightweight Skin Lesion Classification Using Dermoscopic Images	Computer Vision and Pattern Recognition (cs.CV)	Yongwei Wang, Yuheng Wang, Tim K. Lee, Chunyan Miao, Z. Jane Wang
2203.11660	Channel Self-Supervision for Online Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Shixiao Fan, Xuan Cheng, Xiaomin Wang, Chun Yang, Pan Deng, Minghui Liu, Jiali Deng, Ming Liu
2203.11932	Dataset Distillation by Matching Training Trajectories	Computer Vision and Pattern Recognition (cs.CV)	George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu
2203.12081	DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification	Computer Vision and Pattern Recognition (cs.CV)	Hongrun Zhang, Yanda Meng, Yitian Zhao, Yihong Qiao, Xiaoyun Yang, Sarah E. Coupland, Yalin Zheng
2203.12244	Scale-Equivalent Distillation for Semi-Supervised Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Qiushan Guo, Yao Mu, Jianyu Chen, Tianqi Wang, Yizhou Yu, Ping Luo
2203.12574	Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal	Computation and Language (cs.CL)	Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan
2203.12742	Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders	Machine Learning (cs.LG)	Samuel Stanton, Wesley Maddox, Nate Gruver, Phillip Maffettone, Emily Delaney, Peyton Greenside, Andrew Gordon Wilson
2203.13064	Ensembling and Knowledge Distilling of Large Sequence Taggers for Grammatical Error Correction	Computation and Language (cs.CL)	Maksym Tarnavskyi, Artem Chernodub, Kostiantyn Omelianchuk
2203.13072	Multitask Emotion Recognition Model with Knowledge Distillation and Task Discriminator	Computer Vision and Pattern Recognition (cs.CV)	Euiseok Jeong, Geesung Oh, Sejoon Lim
2203.13318	NPBG++: Accelerating Neural Point-Based Graphics	Computer Vision and Pattern Recognition (cs.CV)	Ruslan Rakhimov, Andrei-Timotei Ardelean, Victor Lempitsky, Evgeny Burnaev
2203.13444	Vision Transformer Compression with Structured Pruning and Low Rank Approximation	Computer Vision and Pattern Recognition (cs.CV)	Ankur Kumar
2203.13452	PCA-Based Knowledge Distillation Towards Lightweight and Content-Style Balanced Photorealistic Style Transfer Models	Computer Vision and Pattern Recognition (cs.CV)	Tai-Yin Chiu, Danna Gurari
2203.13616	Lightweight Graph Convolutional Networks with Topologically Consistent Magnitude Pruning	Machine Learning (cs.LG)	Hichem Sahbi
2203.13708	LAMBDA: Covering the Solution Set of Black-Box Inequality by Search Space Quantization	Machine Learning (cs.LG)	Lihao Liu, Tianyue Feng, Xingyu Xing, Junyi Chen
2203.14001	Knowledge Distillation with the Reused Teacher Classifier	Computer Vision and Pattern Recognition (cs.CV)	Defang Chen, Jian-Ping Mei, Hailin Zhang, Can Wang, Yan Feng, Chun Chen
2203.14098	Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Guanglei Yang, Enrico Fini, Dan Xu, Paolo Rota, Mingli Ding, Moin Nabi, Xavier Alameda-Pineda, Elisa Ricci
2203.14169	AutoTS: Automatic Time Series Forecasting Model Design Based on Two-Stage Pruning	Machine Learning (cs.LG)	Chunnan Wang, Xingyu Chen, Chengyue Wu, Hongzhi Wang
2203.14328	On the Neural Tangent Kernel Analysis of Randomly Pruned Wide Neural Networks	Machine Learning (cs.LG)	Hongru Yang, Zhangyang Wang
2203.14642	SPIQ: Data-Free Per-Channel Static Input Quantization	Computer Vision and Pattern Recognition (cs.CV)	Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly
2203.14645	REx: Data-Free Residual Quantization Error Expansion	Computer Vision and Pattern Recognition (cs.CV)	Edouard Yvinec, Arnaud Dapgony, Matthieu Cord, Kevin Bailly
2203.14649	Knowledge Distillation: Bad Models Can Be Good Role Models	Machine Learning (cs.LG)	Gal Kaplun, Eran Malach, Preetum Nakkiran, Shai Shalev-Shwartz
2203.14768	Pruning In Time (PIT): A Lightweight Network Architecture Optimizer for Temporal Convolutional Networks	Machine Learning (cs.LG)	Matteo Risso, Alessio Burrello, Daniele Jahier Pagliari, Francesco Conti, Lorenzo Lamberti, Enrico Macii, Luca Benini, Massimo Poncino
2203.14956	LiDAR Distillation: Bridging the Beam-Induced Domain Gap for 3D Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Yi Wei, Zibu Wei, Yongming Rao, Jiaxin Li, Jie Zhou, Jiwen Lu
2203.15328	Compact Token Representations with Contextual Quantization for Efficient Document Re-ranking	Information Retrieval (cs.IR)	Yingrui Yang, Yifan Qiao, Tao Yang
2203.15401	Neural Face Video Compression using Multiple Views	Computer Vision and Pattern Recognition (cs.CV)	Anna Volokitin, Stefan Brugger, Ali Benlalah, Sebastian Martin, Brian Amberg, Michael Tschannen
2203.15751	A Passive Similarity based CNN Filter Pruning for Efficient Acoustic Scene Classification	Audio and Speech Processing (eess.AS)	Arshdeep Singh, Mark D. Plumbley
2203.15778	Text-Driven Video Acceleration: A Weakly-Supervised Reinforcement Learning Method	Computer Vision and Pattern Recognition (cs.CV)	Washington Ramos, Michel Silva, Edson Araujo, Victor Moura, Keller Oliveira, Leandro Soriano Marcolino, Erickson R. Nascimento
2203.15794	CHEX: CHannel EXploration for CNN Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Zejiang Hou, Minghai Qin, Fei Sun, Xiaolong Ma, Kun Yuan, Yi Xu, Yen-Kuang Chen, Rong Jin, Yuan Xie, Sun-Yuan Kung
2203.15837	Learning to Collide: Recommendation System Model Compression with Learned Hash Functions	Information Retrieval (cs.IR)	Benjamin Ghaemmaghami, Mustafa Ozdal, Rakesh Komuravelli, Dmitriy Korchev, Dheevatsa Mudigere, Krishnakumar Nair, Maxim Naumov
2203.15952	4-bit Conformer with Native Quantization Aware Training for Speech Recognition	Audio and Speech Processing (eess.AS)	Shaojin Ding, Phoenix Meadowlark, Yanzhang He, Lukasz Lew, Shivani Agrawal, Oleg Rybakov
2203.15975	Device-Directed Speech Detection: Regularization via Distillation for Weakly-Supervised Models	Audio and Speech Processing (eess.AS)	Vineet Garg, Ognjen Rudovic, Pranay Dighe, Ahmed H. Abdelaziz, Erik Marchi, Saurabh Adya, Chandra Dhir, Ahmed Tewfik
2203.15996	TextPruner: A Model Pruning Toolkit for Pre-Trained Language Models	Computation and Language (cs.CL)	Ziqing Yang, Yiming Cui, Zhigang Chen
2203.16004	Theory of Acceleration of Decision Making by Correlated Time Sequences	Machine Learning (cs.LG)	Norihiro Okada, Tomoki Yamagami, Nicolas Chauvet, Yusuke Ito, Mikio Hasegawa, Makoto Naruse
2203.16034	Monitored Distillation for Positive Congruent Depth Completion	Computer Vision and Pattern Recognition (cs.CV)	Tian Yu Liu, Parth Agrawal, Allison Chen, Byung-Woo Hong, Alex Wong
2203.16172	Self-Distillation from the Last Mini-Batch for Consistency Regularization	Computer Vision and Pattern Recognition (cs.CV)	Yiqing Shen, Liwu Xu, Yuzhe Yang, Yaqian Li, Yandong Guo
2203.16258	Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data	Computer Vision and Pattern Recognition (cs.CV)	Corentin Sautier, Gilles Puy, Spyros Gidaris, Alexandre Boulch, Andrei Bursuc, Renaud Marlet
2203.16406	PerfectDou: Dominating DouDizhu with Perfect Information Distillation	Artificial Intelligence (cs.AI)	Yang Guan, Minghuan Liu, Weijun Hong, Weinan Zhang, Fei Fang, Guangjun Zeng, Yue Lin
2203.16798	Ternary and Binary Quantization for Improved Classification	Computer Vision and Pattern Recognition (cs.CV)	Weizhi Lu, Mingrui Chen, Kai Guo, Weiyu Li
2203.16965	PADA: Pruning Assisted Domain Adaptation for Self-Supervised Speech Representations	Computation and Language (cs.CL)	Lodagala V S V Durga Prasad, Sreyan Ghosh, S. Umesh
2203.16983	Self-distillation Augmented Masked Autoencoders for Histopathological Image Classification	Computer Vision and Pattern Recognition (cs.CV)	Yang Luo, Zhineng Chen, Xieping Gao
2203.17008	It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher	Computer Vision and Pattern Recognition (cs.CV)	Kanghyun Choi, Hye Yoon Lee, Deokki Hong, Joonsang Yu, Noseong Park, Youngsok Kim, Jinho Lee
2203.17261	R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis	Computer Vision and Pattern Recognition (cs.CV)	Huan Wang, Jian Ren, Zeng Huang, Kyle Olszewski, Menglei Chai, Yun Fu, Sergey Tulyakov
2204.00185	Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings	Information Retrieval (cs.IR)	Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Defu Lian, Yeyun Gong, Qi Chen, Fan Yang, Hao Sun, Yingxia Shao, Denvy Deng, Qi Zhang, Xing Xie
2204.00270	Rethinking Position Bias Modeling with Knowledge Distillation for CTR Prediction	Information Retrieval (cs.IR)	Congcong Liu, Yuejiang Li, Jian Zhu, Xiwei Zhao, Changping Peng, Zhangang Lin, Jingping Shao
2204.00408	Structured Pruning Learns Compact and Accurate Models	Computation and Language (cs.CL)	Mengzhou Xia, Zexuan Zhong, Danqi Chen
2204.00548	Unified and Effective Ensemble Knowledge Distillation	Machine Learning (cs.LG)	Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang
2204.00649	Knowledge distillation with error-correcting transfer learning for wind power prediction	Machine Learning (cs.LG)	Hao Chen
2204.00711	TAC: Optimizing Error-Bounded Lossy Compression for Three-Dimensional Adaptive Mesh Refinement Simulations	Distributed, Parallel, and Cluster Computing (cs.DC)	Daoce Wang, Jesus Pulido, Pascal Grosset, Sian Jin, Jiannan Tian, James Ahrens, Dingwen Tao
2204.00771	Fast Real-time Personalized Speech Enhancement: End-to-End Enhancement Network (E3Net) and Knowledge Distillation	Audio and Speech Processing (eess.AS)	Manthan Thakker, Sefik Emre Eskimez, Takuya Yoshioka, Huaming Wang
2204.00783	Paoding: Supervised Robustness-preserving Data-free Neural Network Pruning	Machine Learning (cs.LG)	Mark Huasong Meng, Guangdong Bai, Sin Gee Teo, Jin Song Dong
2204.00895	Class-Incremental Learning by Knowledge Distillation with Adaptive Feature Consolidation	Machine Learning (cs.LG)	Minsoo Kang, Jaeyoo Park, Bohyung Han
2204.01273	FedSynth: Gradient Compression via Synthetic Data in Federated Learning	Machine Learning (cs.LG)	Shengyuan Hu, Jack Goetz, Kshitiz Malik, Hongyuan Zhan, Zhe Liu, Yue Liu
2204.01385	Aligned Weight Regularizers for Pruning Pretrained Neural Networks	Computation and Language (cs.CL)	James O' Neill, Sourav Dutta, Haytham Assem
2204.01407	Re-examining Distillation For Continual Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Eli Verwimp, Kuo Yang, Sarah Parisot, Hong Lanqing, Steven McDonagh, Eduardo Pérez-Pellitero, Matthias De Lange, Tinne Tuytelaars
2204.01640	APP: Anytime Progressive Pruning	Machine Learning (cs.LG)	Diganta Misra, Bharat Runwal, Tianlong Chen, Zhangyang Wang, Irina Rish
2204.01705	Learning to Accelerate by the Methods of Step-size Planning	Machine Learning (cs.LG)	Hengshuai Yao
2204.01971	Non-Local Latent Relation Distillation for Self-Adaptive 3D Human Pose Estimation	Computer Vision and Pattern Recognition (cs.CV)	Jogendra Nath Kundu, Siddharth Seth, Anirudh Jamkhandi, Pradyumna YM, Varun Jampani, Anirban Chakraborty, R. Venkatesh Babu
2204.02136	Overcoming Catastrophic Forgetting in Incremental Object Detection via Elastic Response Distillation	Computer Vision and Pattern Recognition (cs.CV)	Tao Feng, Mang Wang, Hangjie Yuan
2204.02351	Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling	Machine Learning (cs.LG)	Mansur Arief, Zhepeng Cen, Zhenyuan Liu, Zhiyuang Huang, Henry Lam, Bo Li, Ding Zhao
2204.02601	Probing Structured Pruning on Multilingual Pre-trained Models: Settings, Algorithms, and Efficiency	Computation and Language (cs.CL)	Yanyang Li, Fuli Luo, Runxin Xu, Songfang Huang, Fei Huang, Liwei Wang
2204.02639	Representation Selective Self-distillation and wav2vec 2.0 Feature Exploration for Spoof-aware Speaker Verification	Audio and Speech Processing (eess.AS)	Jin Woo Lee, Eungbeom Kim, Junghyun Koo, Kyogu Lee
2204.02662	Accelerating Backward Aggregation in GCN Training with Execution Path Preparing on GPUs	Machine Learning (cs.LG)	Shaoxian Xu, Zhiyuan Shao, Ci Yang, Xiaofei Liao, Hai Jin
2204.02735	Distilling Robust and Non-Robust Features in Adversarial Examples by Information Bottleneck	Machine Learning (cs.LG)	Junho Kim, Byung-Kwan Lee, Yong Man Ro
2204.02906	Knowledge Base Index Compression via Dimensionality and Precision Reduction	Information Retrieval (cs.IR)	Vilém Zouhar, Marius Mosbach, Miaoran Zhang, Dietrich Klakow
2204.02965	LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification	Computer Vision and Pattern Recognition (cs.CV)	Sharath Girish, Kamal Gupta, Saurabh Singh, Abhinav Shrivastava
2204.03227	Accelerating Attention through Gradient-Based Learned Runtime Pruning	Computation and Language (cs.CL)	Zheng Li, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Mingu Kang
2204.03479	Delta Keyword Transformer: Bringing Transformers to the Edge through Dynamically Pruned Multi-Head Self-Attention	Computation and Language (cs.CL)	Zuzana Jelčicová, Marian Verhelst
2204.03541	End-to-End Zero-Shot HOI Detection via Vision and Language Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Mingrui Wu, Jiaxin Gu, Yunhang Shen, Mingbao Lin, Chao Chen, Xiaoshuai Sun, Rongrong Ji
2204.03642	Pre-train, Self-train, Distill: A simple recipe for Supersizing 3D Reconstruction	Computer Vision and Pattern Recognition (cs.CV)	Kalyan Vasudev Alwala, Abhinav Gupta, Shubham Tulsiani
2204.03778	Mitigating Mismatch Compression in Differential Local Field Potentials	Signal Processing (eess.SP)	Vineet Tiruvadi, Sam James, Bryan Howell, Mosadoluwa Obatusin, Andrea Crowell, Patricio Riva-Posse, Ki Sueng Choi, Allison Waters, Robert E. Gross, Cameron C. McIntyre, Helen S. Mayberg, Robert Butera
2204.03880	CD$^2$-pFed: Cyclic Distillation-guided Channel Decoupling for Model Personalization in Federated Learning	Computer Vision and Pattern Recognition (cs.CV)	Yiqing Shen, Yuyin Zhou, Lequan Yu
2204.04215	Data-Free Quantization with Accurate Activation Clipping and Adaptive Batch Normalization	Machine Learning (cs.LG)	Yefei He, Luoming Zhang, Weijia Wu, Hong Zhou
2204.04375	Channel Pruning In Quantization-aware Training: An Adaptive Projection-gradient Descent-shrinkage-splitting Method	Machine Learning (cs.LG)	Zhijian Li, Jack Xin
2204.04390	Deep neural network goes lighter: A case study of deep compression techniques on automatic RF modulation recognition for Beyond 5G networks	Machine Learning (cs.LG)	Anu Jagannath, Jithin Jagannath, Yanzhi Wang, Tommaso Melodia
2204.04588	Robust Cross-Modal Representation Learning with Progressive Self-Distillation	Computer Vision and Pattern Recognition (cs.CV)	Alex Andonian, Shixing Chen, Raffay Hamid
2204.04662	FOSTER: Feature Boosting and Compression for Class-Incremental Learning	Computer Vision and Pattern Recognition (cs.CV)	Fu-Yun Wang, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan
2204.04977	Regularization-based Pruning of Irrelevant Weights in Deep Neural Architectures	Computation and Language (cs.CL)	Giovanni Bonetta, Matteo Ribero, Rossella Cancelliere
2204.05274	MIME: Adapting a Single Neural Network for Multi-task Inference with Memory-efficient Dynamic Pruning	Machine Learning (cs.LG)	Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Abhishek Moitra, Priyadarshini Panda
2204.05397	Accelerated Design and Deployment of Low-Carbon Concrete for Data Centers	Artificial Intelligence (cs.AI)	Xiou Ge, Richard T. Goodwin, Haizi Yu, Pablo Romero, Omar Abdelrahman, Amruta Sudhalkar, Julius Kusuma, Ryan Cialdella, Nishant Garg, Lav R. Varshney
2204.05502	CoupleFace: Relation Matters for Face Recognition Distillation	Computer Vision and Pattern Recognition (cs.CV)	Jiaheng Liu, Haoyu Qin, Yichao Wu, Jinyang Guo, Ding Liang, Ke Xu
2204.05547	DistPro: Searching A Fast Knowledge Distillation Process via Meta Optimization	Computer Vision and Pattern Recognition (cs.CV)	Xueqing Deng, Dawei Sun, Shawn Newsam, Peng Wang
2204.05580	Codec Compression Efficiency Evaluation of MPEG-5 part 2 (LCEVC) using Objective and Subjective Quality Assessment	Multimedia (cs.MM)	Nabajeet Barman, Steven Schmidt, Saman Zadtootaghaj, Maria G Martini
2204.05639	Neural Network Pruning by Cooperative Coevolution	Neural and Evolutionary Computing (cs.NE)	Haopu Shang, Jia-Liang Wu, Wenjing Hong, Chao Qian
2204.05957	Localization Distillation for Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Zhaohui Zheng, Rongguang Ye, Qibin Hou, Dongwei Ren, Ping Wang, Wangmeng Zuo, Ming-Ming Cheng
2204.06322	Production federated keyword spotting via distillation, filtering, and joint federated-centralized training	Audio and Speech Processing (eess.AS)	Andrew Hard, Kurt Partridge, Neng Chen, Sean Augenstein, Aishanee Shah, Hyun Jin Park, Alex Park, Sara Ng, Jessica Nguyen, Ignacio Lopez Moreno, Rajiv Mathews, Françoise Beaufays
2204.06404	Receding Neuron Importances for Structured Pruning	Machine Learning (cs.LG)	Mihai Suteu, Yike Guo
2204.06652	Joint Coreset Construction and Quantization for Distributed Machine Learning	Machine Learning (cs.LG)	Hanlin Lu, Changchang Liu, Shiqiang Wang, Ting He, Vijay Narayanan, Kevin S. Chan, Stephen Pasteris
2204.06760	HCFL: A High Compression Approach for Communication-Efficient Federated Learning in Very Large Scale IoT Networks	Machine Learning (cs.LG)	Minh-Duong Nguyen, Sang-Min Lee, Quoc-Viet Pham, Dinh Thai Hoang, Diep N. Nguyen, Won-Joo Hwang
2204.06787	Sign Bit is Enough: A Learning Synchronization Framework for Multi-hop All-reduce with Ultimate Compression	Machine Learning (cs.LG)	Feijie Wu, Shiqi He, Song Guo, Zhihao Qu, Haozhao Wang, Weihua Zhuang, Jie Zhang
2204.06899	Spatial Likelihood Voting with Self-Knowledge Distillation for Weakly Supervised Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Ze Chen, Zhihang Fu, Jianqiang Huang, Mingyuan Tao, Rongxin Jiang, Xiang Tian, Yaowu Chen, Xian-sheng Hua
2204.06979	HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising Package	Computer Vision and Pattern Recognition (cs.CV)	Daniel Coquelin, Behnood Rasti, Markus Götz, Pedram Ghamisi, Richard Gloaguen, Achim Streit
2204.06986	Cross-Image Relational Knowledge Distillation for Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Chuanguang Yang, Helong Zhou, Zhulin An, Xue Jiang, Yongjun Xu, Qian Zhang
2204.07028	Exploring the Distributed Knowledge Congruence in Proxy-data-free Federated Distillation	Machine Learning (cs.LG)	Zhiyuan Wu, Sheng Sun, Yuwei Wang, Min Liu, Qingxiang Liu
2204.07137	Accelerated Policy Learning with Parallel Differentiable Simulation	Machine Learning (cs.LG)	Jie Xu, Viktor Makoviychuk, Yashraj Narang, Fabio Ramos, Wojciech Matusik, Animesh Garg, Miles Macklin
2204.07154	MiniViT: Compressing Vision Transformers with Weight Multiplexing	Computer Vision and Pattern Recognition (cs.CV)	Jinnian Zhang, Houwen Peng, Kan Wu, Mengchen Liu, Bin Xiao, Jianlong Fu, Lu Yuan
2204.07316	XDBERT: Distilling Visual Information to BERT from Cross-Modal Systems to Improve Language Understanding	Computation and Language (cs.CL)	Chan-Jan Hsu, Hung-yi Lee, Yu Tsao
2204.07412	End-to-End Sensitivity-Based Filter Pruning	Computer Vision and Pattern Recognition (cs.CV)	Zahra Babaiee, Lucas Liebenwein, Ramin Hasani, Daniela Rus, Radu Grosu
2204.07674	CILDA: Contrastive Data Augmentation using Intermediate Layer Knowledge Distillation	Computation and Language (cs.CL)	Md Akmal Haidar, Mehdi Rezagholizadeh, Abbas Ghaddar, Khalil Bibi, Philippe Langlais, Pascal Poupart
2204.08211	How to Attain Communication-Efficient DNN Training? Convert, Compress, Correct	Machine Learning (cs.LG)	Zhong-Jing Chen, Eduin E. Hernandez, Yu-Chih Huang, Stefano Rini
2204.08306	A Convergence Analysis of Nesterov's Accelerated Gradient Method in Training Deep Linear Neural Networks	Machine Learning (cs.LG)	Xin Liu, Wei Tao, Zhisong Pan
2204.08759	Edge-enhanced Feature Distillation Network for Efficient Super-Resolution	Computer Vision and Pattern Recognition (cs.CV)	Yan Wang
2204.08910	Adaptable Semantic Compression and Resource Allocation for Task-Oriented Communications	Signal Processing (eess.SP)	Chuanhong Liu, Caili Guo, Yang Yang, Nan Jiang
2204.08922	Feature Structure Distillation for BERT Transferring	Computation and Language (cs.CL)	Hee-Jun Jung, Doyeon Kim, Seung-Hoon Na, Kangil Kim
2204.09186	Reconstruction-Aware Prior Distillation for Semi-supervised Point Cloud Completion	Computer Vision and Pattern Recognition (cs.CV)	Zhaoxin Fan, Yulin He, Zhicheng Wang, Kejian Wu, Hongyan Liu, Jun He
2204.09429	HRPose: Real-Time High-Resolution 6D Pose Estimation Network Using Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Qi Guan, Zihao Sheng, Shibei Xue
2204.09656	A Fast Post-Training Pruning Framework for Transformers	Computation and Language (cs.CL)	Woosuk Kwon, Sehoon Kim, Michael W. Mahoney, Joseph Hassoun, Kurt Keutzer, Amir Gholami
2204.09931	Multi-scale Knowledge Distillation for Unsupervised Person Re-Identification	Computer Vision and Pattern Recognition (cs.CV)	Long Lan, Xiao Teng, Haoang Chi, Xiang Zhang
2204.09975	Eliminating Backdoor Triggers for Deep Neural Networks Using Attention Relation Graph Distillation	Machine Learning (cs.LG)	Jun Xia, Ting Wang, Jiepin Ding, Xian Wei, Mingsong Chen
2204.09992	Arbitrary Bit-width Network: A Joint Layer-Wise Quantization and Adaptive Inference Approach	Computer Vision and Pattern Recognition (cs.CV)	Chen Tang, Haoyu Zhai, Kai Ouyang, Zhi Wang, Yifei Zhu, Wenwu Zhu
2204.10323	Accelerating Physics Simulations with TPUs: An Inundation Modeling Example	Distributed, Parallel, and Cluster Computing (cs.DC)	Damien Pierce, R. Lily Hu, Yusef Shafi, Anudhyan Boral, Vladimir Anisimov, Sella Nevo, Yi-fan Chen
2204.10496	Multimodal Adaptive Distillation for Leveraging Unimodal Encoders for Vision-Language Tasks	Computer Vision and Pattern Recognition (cs.CV)	Zhecan Wang, Noel Codella, Yen-Chun Chen, Luowei Zhou, Xiyang Dai, Bin Xiao, Jianwei Yang, Haoxuan You, Kai-Wei Chang, Shih-fu Chang, Lu Yuan
2204.10546	Depth Pruning with Auxiliary Networks for TinyML	Machine Learning (cs.LG)	Josen Daniel De Leon, Rowel Atienza
2204.10579	Lossy compression of matrices by black-box optimisation of mixed-integer non-linear programming	Machine Learning (cs.LG)	Tadashi Kadowaki, Mitsuru Ambai
2204.10788	Towards Accelerated Localization Performance Across Indoor Positioning Datasets	Signal Processing (eess.SP)	Lucie Klus, Darwin Quezada-Gaibor, Joaquın Torres-Sospedra, Elena Simona Lohan, Carlos Granell, Jari Nurmi
2204.10888	Compressibility: Power of PCA in Clustering Problems Beyond Dimensionality Reduction	Machine Learning (cs.LG)	Chandra Sekhar Mukherjee, Jiapeng Zhang
2204.11091	On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation	Information Retrieval (cs.IR)	Xin Xia, Hongzhi Yin, Junliang Yu, Qinyong Wang, Guandong Xu, Nguyen Quoc Viet Hung
2204.11224	Optimizing Task Placement and Online Scheduling for Distributed GNN Training Acceleration	Distributed, Parallel, and Cluster Computing (cs.DC)	Ziyue Luo, Yixin Bao, Chuan Wu
2204.11315	Compression-Based Optimizations for Out-of-Core GPU Stencil Computation	Distributed, Parallel, and Cluster Computing (cs.DC)	Jingcheng Shen, Xin Deng, Yifan Wu, Masao Okita, Fumihiko Ino
2204.11444	Fine-tuning Pruned Networks with Linear Over-parameterization	Computer Vision and Pattern Recognition (cs.CV)	Siyuan Pan, Xiaoshuang Li, Tingyao Li, Liang Hou, Kaibin Qiu, Xiaobing Tu
2204.11463	IMDeception: Grouped Information Distilling Super-Resolution Network	Computer Vision and Pattern Recognition (cs.CV)	Mustafa Ayazoglu
2204.11526	Faculty Distillation with Optimal Transport	Machine Learning (cs.LG)	Su Lu, Han-Jia Ye, De-Chuan Zhan
2204.11536	FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server	Distributed, Parallel, and Cluster Computing (cs.DC)	Hong Zhang, Ji Liu, Juncheng Jia, Yang Zhou, Huaiyu Dai, Dejing Dou
2204.11667	Multi-Head Distillation for Continual Unsupervised Domain Adaptation in Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Antoine Saporta, Arthur Douillard, Tuan-Hung Vu, Patrick Pérez, Matthieu Cord
2204.11723	4DAC: Learning Attribute Compression for Dynamic Point Clouds	Computer Vision and Pattern Recognition (cs.CV)	Guangchi Fang, Qingyong Hu, Yiling Xu, Yulan Guo
2204.11834	Accelerating Machine Learning via the Weber-Fechner Law	Machine Learning (cs.LG)	B.N. Kausik
2204.12091	Gridless Tomographic SAR Imaging Based on Accelerated Atomic Norm Minimization with Efficiency	Signal Processing (eess.SP)	Silin Gao, Zhe Zhang, Bingchen Zhang, Yirong Wu
2204.12322	RAPQ: Rescuing Accuracy for Power-of-Two Low-bit Post-training Quantization	Computer Vision and Pattern Recognition (cs.CV)	Hongyi Yao, Pu Li, Jian Cao, Xiangcheng Liu, Chenying Xie, Bingzhang Wang
2204.12947	Edge-PRUNE: Flexible Distributed Deep Learning Inference	Distributed, Parallel, and Cluster Computing (cs.DC)	Jani Boutellier, Bo Tan, Jari Nurmi
2204.12997	DearKD: Data-Efficient Early Knowledge Distillation for Vision Transformers	Computer Vision and Pattern Recognition (cs.CV)	Xianing Chen, Qiong Cao, Yujie Zhong, Jing Zhang, Shenghua Gao, Dacheng Tao
2204.13511	RobBERTje: a Distilled Dutch BERT Model	Computation and Language (cs.CL)	Pieter Delobelle, Thomas Winters, Bettina Berendt
2204.13679	Curriculum Learning for Dense Retrieval Distillation	Information Retrieval (cs.IR)	Hansi Zeng, Hamed Zamani, Vishwa Vinay
2204.13699	Channel Pruned YOLOv5-based Deep Learning Approach for Rapid and Accurate Outdoor Obstacles Detection	Computer Vision and Pattern Recognition (cs.CV)	Zeqian Li, Keyu Qiu, Zhibin Yu
2204.13873	Multiple Degradation and Reconstruction Network for Single Image Denoising via Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Juncheng Li, Hanhui Yang, Qiaosi Yi, Faming Fang, Guangwei Gao, Tieyong Zeng, Guixu Zhang
2204.13913	Leaner and Faster: Two-Stage Model Compression for Lightweight Text-Image Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Siyu Ren, Kenny Q. Zhu
2205.00172	FEDIC: Federated Learning on Non-IID and Long-Tailed Data via Calibrated Distillation	Machine Learning (cs.LG)	Xinyi Shang, Yang Lu, Yiu-ming Cheung, Hanzi Wang
2205.00179	ClusterQ: Semantic Feature Distribution Alignment for Data-Free Quantization	Computer Vision and Pattern Recognition (cs.CV)	Yangcheng Gao, Zhao Zhang, Richang Hong, Haijun Zhang, Jicong Fan, Shuicheng Yan, Meng Wang
2205.00479	Nearest Neighbor Knowledge Distillation for Neural Machine Translation	Computation and Language (cs.CL)	Zhixian Yang, Renliang Sun, Xiaojun Wan
2205.00506	Preserve Pre-trained Knowledge: Transfer Learning With Self-Distillation For Action Recognition	Computer Vision and Pattern Recognition (cs.CV)	Yang Zhou, Zhanhao He, Keyu Lu, Guanhong Wang, Gaoang Wang
2205.00548	Large-Scale Multi-Document Summarization with Information Extraction and Compression	Computation and Language (cs.CL)	Ning Wang, Han Liu, Diego Klabjan
2205.00706	FedDKD: Federated Learning with Decentralized Knowledge Distillation	Machine Learning (cs.LG)	Xinjia Li, Boyu Chen, Wenlian Lu
2205.00858	Cross-Domain Correlation Distillation for Unsupervised Domain Adaptation in Nighttime Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Huan Gao, Jichang Guo, Guoli Wang, Qian Zhang
2205.01088	Ensemble pruning via an integer programming approach with diversity constraints	Machine Learning (cs.LG)	Marcelo Antônio Mendes Bastos, Humberto Brandão César de Oliveira, Cristiano Arbex Valle
2205.01291	Cross Domain Object Detection by Target-Perceived Dual Branch Distillation	Computer Vision and Pattern Recognition (cs.CV)	Mengzhe He, Yali Wang, Jiaxi Wu, Yiru Wang, Hanqing Li, Bo Li, Weihao Gan, Wei Wu, Yu Qiao
2205.01314	Distilling Governing Laws and Source Input for Dynamical Systems from Videos	Computer Vision and Pattern Recognition (cs.CV)	Lele Luan, Yang Liu, Hao Sun
2205.01529	Masked Generative Distillation	Computer Vision and Pattern Recognition (cs.CV)	Zhendong Yang, Zhe Li, Mingqi Shao, Dachuan Shi, Zehuan Yuan, Chun Yuan
2205.01620	OmniKnight: Multilingual Neural Machine Translation with Language-Specific Self-Distillation	Computation and Language (cs.CL)	Yichong Huang, Xiaocheng Feng, Xinwei Geng, Bing Qin
2205.01915	Generalized Knowledge Distillation via Relationship Matching	Computer Vision and Pattern Recognition (cs.CV)	Han-Jia Ye, Su Lu, De-Chuan Zhan
2205.01997	Attention-based Knowledge Distillation in Multi-attention Tasks: The Impact of a DCT-driven Loss	Computer Vision and Pattern Recognition (cs.CV)	Alejandro López-Cifuentes, Marcos Escudero-Viñolo, Jesús Bescós, Juan C. SanMiguel
2205.02340	Knowledge Distillation of Russian Language Models with Reduction of Vocabulary	Computation and Language (cs.CL)	Alina Kolesnikova, Yuri Kuratov, Vasily Konovalov, Mikhail Burtsev
2205.02359	FedSPLIT: One-Shot Federated Recommendation System Based on Non-negative Joint Matrix Factorization and Knowledge Distillation	Machine Learning (cs.LG)	Maksim E. Eren, Luke E. Richards, Manish Bhattarai, Roberto Yus, Charles Nicholas, Boian S. Alexandrov
2205.02399	Spot-adaptive Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Jie Song, Ying Chen, Jingwen Ye, Mingli Song
2205.02410	Dynamic Bayesian Network Auxiliary ABC-SMC for Hybrid Model Bayesian Inference to Accelerate Biomanufacturing Process Mechanism Learning and Robust Control	Machine Learning (stat.ML)	Wei Xie, Keqi Wang, Hua Zheng, Ben Feng
2205.02795	Diversifying Neural Dialogue Generation via Negative Distillation	Computation and Language (cs.CL)	Yiwei Li, Shaoxiong Feng, Bin Sun, Kan Li
2205.02930	FisheyeDistill: Self-Supervised Monocular Depth Estimation with Ordinal Distillation for Fisheye Cameras	Computer Vision and Pattern Recognition (cs.CV)	Qingan Yan, Pan Ji, Nitin Bansal, Yuxin Ma, Yuan Tian, Yi Xu
2205.02976	Variance Reduction based Partial Trajectory Reuse to Accelerate Policy Gradient Optimization	Machine Learning (cs.LG)	Hua Zheng, Wei Xie
2205.03184	Green Accelerated Hoeffding Tree	Machine Learning (cs.LG)	Eva Garcia-Martin, Albert Bifet, Niklas Lavesson, Rikard König, Henrik Linusson
2205.03307	Forget Less, Count Better: A Domain-Incremental Self-Distillation Learning Benchmark for Lifelong Crowd Counting	Computer Vision and Pattern Recognition (cs.CV)	Jiaqi Gao, Jingqi Li, Hongming Shan, Yanyun Qu, James Z. Wang, Junping Zhang
2205.03494	Online Model Compression for Federated Learning with Large Models	Machine Learning (cs.LG)	Tien-Ju Yang, Yonghui Xiao, Giovanni Motta, Françoise Beaufays, Rajiv Mathews, Mingqing Chen
2205.03601	ConceptDistil: Model-Agnostic Distillation of Concept Explanations	Machine Learning (cs.LG)	João Bento Sousa, Ricardo Moreira, Vladimir Balayan, Pedro Saleiro, Pedro Bizarro
2205.03602	Automatic Block-wise Pruning with Auxiliary Gating Structures for Deep Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Zhaofeng Si, Honggang Qi, Xiaoyu Song
2205.03650	Distilling Inter-Class Distance for Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Zhengbo Zhang, Chunluan Zhou, Zhigang Tu
2205.03773	Mutual Distillation Learning Network for Trajectory-User Linking	Machine Learning (cs.LG)	Wei Chen, Shuzhe Li, Chao Huang, Yanwei Yu, Yongguo Jiang, Junyu Dong
2205.03779	Communication Compression for Decentralized Learning with Operator Splitting Methods	Machine Learning (cs.LG)	Yuki Takezawa, Kenta Niwa, Makoto Yamada
2205.03792	One-Class Knowledge Distillation for Face Presentation Attack Detection	Computer Vision and Pattern Recognition (cs.CV)	Zhi Li, Rizhao Cai, Haoliang Li, Kwok-Yan Lam, Yongjian Hu, Alex C. Kot
2205.03811	Data-Free Adversarial Knowledge Distillation for Graph Neural Networks	Machine Learning (cs.LG)	Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi, Carl Yang, Lichao Sun
2205.03914	Federated Random Reshuffling with Compression and Variance Reduction	Machine Learning (cs.LG)	Grigory Malinovsky, Peter Richtárik
2205.04157	Attribution-based Task-specific Pruning for Multi-task Language Models	Computation and Language (cs.CL)	Nakyeong Yang, Yunah Jang, Hwanhee Lee, Seohyeong Jung, Kyomin Jung
2205.04180	EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization	Machine Learning (cs.LG)	Laurent Condat, Kai Yi, Peter Richtárik
2205.04733	From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective	Information Retrieval (cs.IR)	Thibault Formal, Carlos Lassance, Benjamin Piwowarski, Stéphane Clinchant
2205.05069	Accelerating the Training of Video Super-Resolution Models	Computer Vision and Pattern Recognition (cs.CV)	Lijian Lin, Xintao Wang, Zhongang Qi, Ying Shan
2205.05365	Slab Track Condition Monitoring Based on Learned Sparse Features from Acoustic and Acceleration Signals	Signal Processing (eess.SP)	Baorui Dai, Gaëtan Frusque, Qi Li, Olga Fink
2205.05476	Contrastive Supervised Distillation for Continual Representation Learning	Computer Vision and Pattern Recognition (cs.CV)	Tommaso Barletti, Niccolo' Biondi, Federico Pernici, Matteo Bruni, Alberto Del Bimbo
2205.05632	On Distributed Adaptive Optimization with Gradient Compression	Machine Learning (stat.ML)	Xiaoyun Li, Belhal Karimi, Ping Li
2205.05676	Revisiting Random Channel Pruning for Neural Network Compression	Computer Vision and Pattern Recognition (cs.CV)	Yawei Li, Kamil Adamczewski, Wen Li, Shuhang Gu, Radu Timofte, Luc Van Gool
2205.05967	Target Aware Network Architecture Search and Compression for Efficient Knowledge Transfer	Computer Vision and Pattern Recognition (cs.CV)	S.H.Shabbeer Basha, Debapriya Tula, Sravan Kumar Vinakota, Shiv Ram Dubey
2205.06237	Knowledge Distillation for Multi-Target Domain Adaptation in Real-Time Person Re-Identification	Computer Vision and Pattern Recognition (cs.CV)	Félix Remigereau, Djebril Mekhazni, Sajjad Abdoli, Le Thanh Nguyen-Meidine, Rafael M. O. Cruz, Eric Granger
2205.06404	Fast Conditional Network Compression Using Bayesian HyperNetworks	Machine Learning (cs.LG)	Phuoc Nguyen, Truyen Tran, Ky Le, Sunil Gupta, Santu Rana, Dang Nguyen, Trong Nguyen, Shannon Ryan, Svetha Venkatesh
2205.06491	OFedQIT: Communication-Efficient Online Federated Learning via Quantization and Intermittent Transmission	Machine Learning (cs.LG)	Jonghwan Park, Dohyeok Kwon, Songnam hong
2205.06701	Knowledge Distillation Meets Open-Set Semi-Supervised Learning	Computer Vision and Pattern Recognition (cs.CV)	Jing Yang, Xiatian Zhu, Adrian Bulat, Brais Martinez, Georgios Tzimiropoulos
2205.06906	Structural Dropout for Model Width Compression	Machine Learning (cs.LG)	Julian Knodt
2205.07523	Prompting to Distill: Boosting Data-Free Knowledge Distillation via Reinforced Prompt	Computation and Language (cs.CL)	Xinyin Ma, Xinchao Wang, Gongfan Fang, Yongliang Shen, Weiming Lu
2205.07547	SQ-VAE: Variational Bayes on Discrete Representation with Self-annealed Stochastic Quantization	Machine Learning (cs.LG)	Yuhta Takida, Takashi Shibuya, WeiHsiang Liao, Chieh-Hsin Lai, Junki Ohmura, Toshimitsu Uesaka, Naoki Murata, Shusuke Takahashi, Toshiyuki Kumakura, Yuki Mitsufuji
2205.07582	Chemical transformer compression for accelerating both training and inference of molecular modeling	Machine Learning (cs.LG)	Yi Yu, Karl Borjesson
2205.07877	A Comprehensive Survey on Model Quantization for Deep Neural Networks	Machine Learning (cs.LG)	Babak Rokh, Ali Azarpeyvand, Alireza Khanteymoori
2205.07976	Accelerating X-Ray Tracing for Exascale Systems using Kokkos	Distributed, Parallel, and Cluster Computing (cs.DC)	Felix Wittwer (1), Nicholas K. Sauter (2), Derek Mendez (2), Billy K. Poon (2), Aaron S. Brewster (2), James M. Holton (2), Michael E. Wall (3), William E. Hart (4), Deborah J. Bard (1), Johannes P. Blaschke (1) ((1) National Energy Research Scientific Computing Center, Lawrence Berkeley National Laboratory, USA, (2) Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, USA, (3) Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, USA, (4) Sandia National Laboratories, USA)
2205.08099	Dimensionality Reduced Training by Pruning and Freezing Parts of a Deep Neural Network, a Survey	Machine Learning (cs.LG)	Paul Wimmer, Jens Mehnert, Alexandru Paul Condurache
2205.08187	Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility	Machine Learning (stat.ML)	Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, François Caron
2205.08358	Perturbation of Deep Autoencoder Weights for Model Compression and Classification of Tabular Data	Machine Learning (cs.LG)	Manar Samad, Sakib Abrar
2205.08668	Learning Monocular Depth Estimation via Selective Distillation of Stereo Knowledge	Computer Vision and Pattern Recognition (cs.CV)	Kyeongseob Song, Kuk-Jin Yoon
2205.08685	Policy Distillation with Selective Input Gradient Regularization for Efficient Interpretability	Machine Learning (cs.LG)	Jinwei Xing, Takashi Nagata, Xinyun Zou, Emre Neftci, Jeffrey L. Krichmar
2205.08695	Hyperparameter Optimization with Neural Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Kangil Lee, Junho Yim
2205.08957	Meta-Learning Sparse Compression Networks	Machine Learning (stat.ML)	Jonathan Richard Schwarz, Yee Whye Teh
2205.09153	ERNIE-Search: Bridging Cross-Encoder with Dual-Encoder via Self On-the-fly Distillation for Dense Passage Retrieval	Computation and Language (cs.CL)	Yuxiang Lu, Yiding Liu, Jiaxiang Liu, Yunsheng Shi, Zhengjie Huang, Shikun Feng Yu Sun, Hao Tian, Hua Wu, Shuaiqiang Wang, Dawei Yin, Haifeng Wang
2205.09292	Free Lunch for Surgical Video Understanding by Distilling Self-Supervisions	Computer Vision and Pattern Recognition (cs.CV)	Xinpeng Ding, Ziwei Liu, Xiaomeng Li
2205.09329	Dataset Pruning: Reducing Training Data by Examining Generalization Influence	Machine Learning (cs.LG)	Shuo Yang, Zeke Xie, Hanyu Peng, Min Xu, Mingming Sun, Ping Li
2205.09332	Accelerated Training of Physics Informed Neural Networks (PINNs) using Meshless Discretizations	Machine Learning (cs.LG)	Ramansh Sharma, Varun Shankar
2205.09526	Simple Regularisation for Uncertainty-Aware Knowledge Distillation	Machine Learning (cs.LG)	Martin Ferianc, Miguel Rodrigues
2205.09638	Certified Error Control of Candidate Set Pruning for Two-Stage Relevance Ranking	Information Retrieval (cs.IR)	Minghan Li, Xinyu Zhang, Ji Xin, Hongyang Zhang, Jimmy Lin
2205.09849	Confident Clustering via PCA Compression Ratio and Its Application to Single-cell RNA-seq Analysis	Machine Learning (cs.LG)	Yingcong Li, Chandra Sekhar Mukherjee, Jiapeng Zhang
2205.10003	InDistill: Transferring Knowledge From Pruned Intermediate Layers	Computer Vision and Pattern Recognition (cs.CV)	Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos, Ioannis Kompatsiaris
2205.10036	Exploring Extreme Parameter Compression for Pre-trained Language Models	Computation and Language (cs.CL)	Yuxin Ren, Benyou Wang, Lifeng Shang, Xin Jiang, Qun Liu
2205.10271	Compression ensembles quantify aesthetic complexity and the evolution of visual art	Computer Vision and Pattern Recognition (cs.CV)	Andres Karjus, Mar Canet Solà, Tillmann Ohm, Sebastian E. Ahnert, Maximilian Schich
2205.10350	Lossless Acceleration for Seq2seq Generation with Aggressive Decoding	Computation and Language (cs.CL)	Tao Ge, Heming Xia, Xin Sun, Si-Qing Chen, Furu Wei
2205.10369	Deployment of Energy-Efficient Deep Learning Models on Cortex-M based Microcontrollers using Deep Compression	Machine Learning (cs.LG)	Mark Deutel, Philipp Woller, Christopher Mutschler, Jürgen Teich
2205.10490	Mapping Emulation for Knowledge Distillation	Machine Learning (cs.LG)	Jing Ma, Xiang Xiang, Zihan Zhang, Yuwen Tan, Yiming Wan, Zhigang Zeng, Dacheng Tao
2205.10536	Knowledge Distillation from A Stronger Teacher	Computer Vision and Pattern Recognition (cs.CV)	Tao Huang, Shan You, Fei Wang, Chen Qian, Chang Xu
2205.10637	Symmetry Teleportation for Accelerated Optimization	Machine Learning (cs.LG)	Bo Zhao, Nima Dehmamy, Robin Walters, Rose Yu
2205.10681	Nonparametric Decentralized Detection and Sparse Sensor Selection via Multi-Sensor Online Kernel Scalar Quantization	Signal Processing (eess.SP)	Jing Guo, Raghu G. Raj, David J. Love, Christopher G. Brinton
2205.10793	Knowledge Distillation via the Target-aware Transformer	Computer Vision and Pattern Recognition (cs.CV)	Sihao Lin, Hongwei Xie, Bing Wang, Kaicheng Yu, Xiaojun Chang, Xiaodan Liang, Gang Wang
2205.10970	Neural Subgraph Explorer: Reducing Noisy Information via Target-Oriented Syntax Graph Pruning	Computation and Language (cs.CL)	Bowen Xing, Ivor W. Tsang
2205.10986	Boosting Multi-Label Image Classification with Complementary Parallel Self-Distillation	Computer Vision and Pattern Recognition (cs.CV)	Jiazhi Xu, Sheng Huang, Fengtao Zhou, Luwen Huangfu, Daniel Zeng, Bo Liu
2205.11055	TempLM: Distilling Language Models into Template-Based Generators	Computation and Language (cs.CL)	Tianyi Zhang, Mina Lee, Lisa Li, Ende Shen, Tatsunori B. Hashimoto
2205.11071	Self-distilled Knowledge Delegator for Exemplar-free Class Incremental Learning	Computer Vision and Pattern Recognition (cs.CV)	Fanfan Ye, Liang Ma, Qiaoyong Zhong, Di Xie, Shiliang Pu
2205.11098	PointDistiller: Structured Knowledge Distillation Towards Efficient and Compact 3D Detection	Computer Vision and Pattern Recognition (cs.CV)	Linfeng Zhang, Runpei Dong, Hung-Shuo Tai, Kaisheng Ma
2205.11100	Supporting Vision-Language Model Inference with Causality-pruning Knowledge Prompt	Computer Vision and Pattern Recognition (cs.CV)	Jiangmeng Li, Wenyi Mo, Wenwen Qiang, Bing Su, Changwen Zheng
2205.11111	DistilCamemBERT: a distillation of the French model CamemBERT	Computation and Language (cs.CL)	Cyrile Delestre, Abibatou Amar
2205.11141	OPQ: Compressing Deep Neural Networks with One-shot Pruning-Quantization	Computer Vision and Pattern Recognition (cs.CV)	Peng Hu, Xi Peng, Hongyuan Zhu, Mohamed M. Sabry Aly, Jie Lin
2205.11158	QEKD: Query-Efficient and Data-Free Knowledge Distillation from Black-box Models	Artificial Intelligence (cs.AI)	Jie Zhang, Chen Chen, Jiahua Dong, Ruoxi Jia, Lingjuan Lyu
2205.11162	A Self-Paced Mixed Distillation Method for Non-Autoregressive Generation	Computation and Language (cs.CL)	Weizhen Qi, Yeyun Gong, Yelong Shen, Jian Jiao, Yu Yan, Houqiang Li, Ruofei Zhang, Weizhu Chen, Nan Duan
2205.11226	Scalable Kernel-Based Minimum Mean Square Error Estimator for Accelerated Image Error Concealment	Computer Vision and Pattern Recognition (cs.CV)	Ján Koloda, Jürgen Seiler, Antonio M. Peinado, André Kaup
2205.11246	[Re] Distilling Knowledge via Knowledge Review	Computer Vision and Pattern Recognition (cs.CV)	Apoorva Verma, Pranjal Gulati, Sarthak Gupta
2205.11284	Few-bit Quantization of Neural Networks for Nonlinearity Mitigation in a Fiber Transmission Experiment	Signal Processing (eess.SP)	Jamal Darweesh (1), Nelson Costa (2), Antonio Napoli (3), Bernhard Spinnler (3), Yves Jaouen (1), Mansoor Yousefi (1). ((1) Telecom-Paris, (2) Infinera, Unipessoal Lda, Carnaxide, Portugal, (3) Infinera, Munich, Germany)
2205.11416	The Importance of Being Parameters: An Intra-Distillation Method for Serious Gains	Computation and Language (cs.CL)	Haoran Xu, Philipp Koehn, Kenton Murray
2205.11440	Federated Distillation based Indoor Localization for IoT Networks	Signal Processing (eess.SP)	Yaya Etiabi, Marwa Chafii, El Mehdi Amhoud
2205.11563	Accelerating the creation of instance segmentation training sets through bounding box annotation	Computer Vision and Pattern Recognition (cs.CV)	Niels Sayez, Christophe De Vleeschouwer
2205.11678	Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation	Machine Learning (cs.LG)	Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu
2205.11845	CDFKD-MFS: Collaborative Data-free Knowledge Distillation via Multi-level Feature Sharing	Computer Vision and Pattern Recognition (cs.CV)	Zhiwei Hao, Yong Luo, Zhi Wang, Han Hu, Jianping An
2205.11854	Multi-Agent Collaborative Inference via DNN Decoupling: Intermediate Feature Compression and Edge Learning	Machine Learning (cs.LG)	Zhiwei Hao, Guanyu Xu, Yong Luo, Han Hu, Jianping An, Shiwen Mao
2205.11921	Compression-aware Training of Neural Networks using Frank-Wolfe	Machine Learning (cs.LG)	Max Zimmer, Christoph Spiegel, Sebastian Pokutta
2205.12258	History Compression via Language Models in Reinforcement Learning	Machine Learning (cs.LG)	Fabian Paischer, Thomas Adler, Vihang Patil, Angela Bitto-Nemling, Markus Holzleitner, Sebastian Lehner, Hamid Eghbal-zadeh, Sepp Hochreiter
2205.12268	Wavelet Feature Maps Compression for Image-to-Image CNNs	Computer Vision and Pattern Recognition (cs.CV)	Shahaf E. Finder, Yair Zohav, Maor Ashkenazi, Eran Treister
2205.12451	Region-aware Knowledge Distillation for Efficient Image-to-Image Translation	Computer Vision and Pattern Recognition (cs.CV)	Linfeng Zhang, Xin Chen, Runpei Dong, Kaisheng Ma
2205.12524	Accelerating Diffusion Models via Early Stop of the Diffusion Process	Computer Vision and Pattern Recognition (cs.CV)	Zhaoyang Lyu, Xudong XU, Ceyuan Yang, Dahua Lin, Bo Dai
2205.12654	Bitext Mining Using Distilled Sentence Representations for Low-Resource Languages	Computation and Language (cs.CL)	Kevin Heffernan, Onur Çelebi, Holger Schwenk
2205.12694	Train Flat, Then Compress: Sharpness-Aware Minimization Learns More Compressible Models	Computation and Language (cs.CL)	Clara Na, Sanket Vaibhav Mehta, Emma Strubell
2205.12840	DistillAdapt: Source-Free Active Visual Domain Adaptation	Computer Vision and Pattern Recognition (cs.CV)	Divya Kothandaraman, Sumit Shekhar, Abhilasha Sancheti, Manoj Ghuhan, Tripti Shukla, Dinesh Manocha
2205.13016	BiT: Robustly Binarized Multi-distilled Transformer	Machine Learning (cs.LG)	Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad
2205.13272	FCN-Pose: A Pruned and Quantized CNN for Robot Pose Estimation for Constrained Devices	Computer Vision and Pattern Recognition (cs.CV)	Marrone Silvério Melo Dantas, Iago Richard Rodrigues, Assis Tiago Oliveira Filho, Gibson Barbosa, Daniel Bezerra, Djamel F. H. Sadok, Judith Kelner, Maria Marquezini, Ricardo Silva
2205.13341	QUIC-FL: Quick Unbiased Compression for Federated Learning	Machine Learning (cs.LG)	Ran Ben Basat, Shay Vargaftik, Amit Portnoy, Gil Einziger, Yaniv Ben-Itzhak, Michael Mitzenmacher
2205.13383	BppAttack: Stealthy and Efficient Trojan Attacks against Deep Neural Networks via Image Quantization and Contrastive Adversarial Learning	Computer Vision and Pattern Recognition (cs.CV)	Zhenting Wang, Juan Zhai, Shiqing Ma
2205.13574	Pruning has a disparate impact on model accuracy	Machine Learning (cs.LG)	Cuong Tran, Ferdinando Fioretto, Jung-Eun Kim, Rakshit Naidu
2205.14141	Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yixuan Wei, Han Hu, Zhenda Xie, Zheng Zhang, Yue Cao, Jianmin Bao, Dong Chen, Baining Guo
2205.14333	One Reference Is Not Enough: Diverse Distillation with Reference Selection for Non-Autoregressive Translation	Computation and Language (cs.CL)	Chenze Shao, Xuanfu Wu, Yang Feng
2205.14465	ByteComp: Revisiting Gradient Compression in Distributed Training	Machine Learning (cs.LG)	Zhuang Wang, Haibin Lin, Yibo Zhu, T. S. Eugene Ng
2205.14570	AutoDisc: Automatic Distillation Schedule for Large Language Model Compression	Computation and Language (cs.CL)	Chen Zhang, Yang Yang, Qifan Wang, Jiahao Liu, Jingang Wang, Wei Wu, Dawei Song
2205.14589	Masked Distillation with Receptive Tokens	Computer Vision and Pattern Recognition (cs.CV)	Tao Huang, Yuan Zhang, Shan You, Fei Wang, Chen Qian, Jian Cao, Chang Xu
2205.14870	Compressible-composable NeRF via Rank-residual Decomposition	Computer Vision and Pattern Recognition (cs.CV)	Jiaxiang Tang, Xiaokang Chen, Jingbo Wang, Gang Zeng
2205.14960	FedAUXfdp: Differentially Private One-Shot Federated Distillation	Machine Learning (cs.LG)	Haley Hoech, Roman Rischke, Karsten Müller, Wojciech Samek
2205.14971	Knowledge Distillation for 6D Pose Estimation by Keypoint Distribution Alignment	Computer Vision and Pattern Recognition (cs.CV)	Shuxuan Guo, Yinlin Hu, Jose M. Alvarez, Mathieu Salzmann
2205.15018	A reconfigurable integrated electronic tongue and its use in accelerated analysis of juices and wines	Machine Learning (cs.LG)	Gianmarco Gabrieli, Michal Muszynski, Patrick W. Ruch
2205.15156	Towards Efficient 3D Object Detection with Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Jihan Yang, Shaoshuai Shi, Runyu Ding, Zhe Wang, Xiaojuan Qi
2205.15171	Parameter Efficient Diff Pruning for Bias Mitigation	Machine Learning (cs.LG)	Lukas Hauzenberger, Navid Rekabsaz
2205.15198	STN: Scalable Tensorizing Networks via Structure-Aware Training and Adaptive Compression	Computer Vision and Pattern Recognition (cs.CV)	Chang Nie, Huan Wang, Lu Zhao
2205.15286	Accelerating spiking neural network training	Neural and Evolutionary Computing (cs.NE)	Luke Taylor, Andrew King, Nicol Harper
2205.15308	Parameter-Efficient and Student-Friendly Knowledge Distillation	Machine Learning (cs.LG)	Jun Rao, Xv Meng, Liang Ding, Shuhan Qi, Dacheng Tao
2205.15404	Gator: Customizable Channel Pruning of Neural Networks with Gating	Computer Vision and Pattern Recognition (cs.CV)	Eli Passov, Eli David, Nathan S. Netanyahu
2205.15437	FBM: Fast-Bit Allocation for Mixed-Precision Quantization	Machine Learning (cs.LG)	Moshe Kimhi, Tal Rozen, Tal Kopetz, Olya Sirkin, Avi Mendelson, Chaim Baskin
2205.15531	itKD: Interchange Transfer-based Knowledge Distillation for 3D Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Hyeon Cho, Junyong Choi, Geonwoo Baek, Wonjun Hwang
2205.15585	Decomposing NeRF for Editing via Feature Field Distillation	Computer Vision and Pattern Recognition (cs.CV)	Sosuke Kobayashi, Eiichi Matsumoto, Vincent Sitzmann
2205.15721	One Loss for Quantization: Deep Hashing with Discrete Wasserstein Distributional Matching	Computer Vision and Pattern Recognition (cs.CV)	Khoa D. Doan, Peng Yang, Ping Li
2205.15731	ViNNPruner: Visual Interactive Pruning for Deep Learning	Machine Learning (cs.LG)	Udo Schlegel, Samuel Schiegg, Daniel A. Keim
2205.16004	What Knowledge Gets Distilled in Knowledge Distillation?	Computer Vision and Pattern Recognition (cs.CV)	Utkarsh Ojha, Yuheng Li, Yong Jae Lee
2206.00128	ForestPrune: Compact Depth-Controlled Tree Ensembles	Machine Learning (stat.ML)	Brian Liu, Rahul Mazumder
2206.00277	Task-Specific Expert Pruning for Sparse Mixture-of-Experts	Machine Learning (cs.LG)	Tianyu Chen, Shaohan Huang, Yuan Xie, Binxing Jiao, Daxin Jiang, Haoyi Zhou, Jianxin Li, Furu Wei
2206.00332	Smart Channel State Information Pre-processing for Joint Authentication and Secret Key Distillation	Signal Processing (eess.SP)	Muralikrishnan Srinivasan, Sotiris Skaperas, Arsenia Chorti, Mahdi Shakiba Herfeh, Muhammad K. Shehzad, Philippe Sehier
2206.00529	Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top	Machine Learning (cs.LG)	Eduard Gorbunov, Samuel Horváth, Peter Richtárik, Gauthier Gidel
2206.00719	Dataset Distillation using Neural Feature Regression	Machine Learning (cs.LG)	Yongchao Zhou, Ehsan Nezhadarya, Jimmy Ba
2206.00809	Distilling Knowledge from Object Classification to Aesthetics Assessment	Multimedia (cs.MM)	Jingwen Hou, Henghui Ding, Weisi Lin, Weide Liu, Yuming Fang
2206.00820	NIPQ: Noise Injection Pseudo Quantization for Automated DNN Optimization	Machine Learning (cs.LG)	Sein Park, Junhyuk So, Juncheol Shin, Eunhyeok Park
2206.00902	MISSU: 3D Medical Image Segmentation via Self-distilling TransUNet	Computer Vision and Pattern Recognition (cs.CV)	Nan Wang, Shaohui Lin, Xiaoxiao Li, Ke Li, Yunhang Shen, Yue Gao, Lizhuang Ma
2206.01186	ORC: Network Group-based Knowledge Distillation using Online Role Change	Machine Learning (cs.LG)	Junyong Choi, Hyeon Cho, Seockhwa Jeong, Wonjun Hwang
2206.01198	Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization	Computer Vision and Pattern Recognition (cs.CV)	Yanyu Li, Pu Zhao, Geng Yuan, Xue Lin, Yanzhi Wang, Xin Chen
2206.01297	Lossless Compression of Point Cloud Sequences Using Sequence Optimized CNN Models	Computer Vision and Pattern Recognition (cs.CV)	Emre Can Kaya, Ioan Tabus
2206.01299	Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees	Machine Learning (cs.LG)	Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Re, Ce Zhang
2206.01538	Accelerating hydrodynamic simulations of urban drainage systems with physics-guided machine learning	Machine Learning (cs.LG)	Rocco Palmitessa, Morten Grum, Allan Peter Engsig-Karup, Roland Löwe
2206.01627	Pruning for Interpretable, Feature-Preserving Circuits in CNNs	Computer Vision and Pattern Recognition (cs.CV)	Chris Hamblin, Talia Konkle, George Alvarez
2206.01640	PROMISSING: Pruning Missing Values in Neural Networks	Machine Learning (cs.LG)	Seyed Mostafa Kia, Nastaran Mohammadian Rad, Daniel van Opstal, Bart van Schie, Andre F. Marquand, Josien Pluim, Wiepke Cahn, Hugo G. Schnack
2206.01838	Differentially Private Model Compression	Machine Learning (cs.LG)	Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin A Inan, Lukas Wutschitz, Janardhan Kulkarni
2206.01859	Extreme Compression for Pre-trained Transformers Made Simple and Efficient	Computation and Language (cs.CL)	Xiaoxia Wu, Zhewei Yao, Minjia Zhang, Conglong Li, Yuxiong He
2206.01861	ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers	Computation and Language (cs.CL)	Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, Xiaoxia Wu, Conglong Li, Yuxiong He
2206.02099	Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Yuenan Hou, Xinge Zhu, Yuexin Ma, Chen Change Loy, Yikang Li
2206.02115	Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation	Information Retrieval (cs.IR)	Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King
2206.02158	Vanilla Feature Distillation for Improving the Accuracy-Robustness Trade-Off in Adversarial Training	Computer Vision and Pattern Recognition (cs.CV)	Guodong Cao, Zhibo Wang, Xiaowei Dong, Zhifei Zhang, Hengchang Guo, Zhan Qin, Kui Ren
2206.02183	Functional Ensemble Distillation	Machine Learning (cs.LG)	Coby Penso, Idan Achituve, Ethan Fetaya
2206.02307	Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-aware Contrastive Distillation	Computer Vision and Pattern Recognition (cs.CV)	Chenyu You, Weicheng Dai, Lawrence Staib, James S. Duncan
2206.02325	Evaluation-oriented Knowledge Distillation for Deep Face Recognition	Computer Vision and Pattern Recognition (cs.CV)	Yuge Huang, Jiaxiang Wu, Xingkun Xu, Shouhong Ding
2206.02531	3D-Augmented Contrastive Knowledge Distillation for Image-based Object Pose Estimation	Computer Vision and Pattern Recognition (cs.CV)	Zhidan Liu, Zhen Xing, Xiangdong Zhou, Yijiang Chen, Guichun Zhou
2206.02873	No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval	Information Retrieval (cs.IR)	Guilherme Moraes Rosa, Luiz Bonifacio, Vitor Jeronymo, Hugo Abonizio, Marzieh Fadaee, Roberto Lotufo, Rodrigo Nogueira
2206.02916	Remember the Past: Distilling Datasets into Addressable Memories for Neural Networks	Machine Learning (cs.LG)	Zhiwei Deng, Olga Russakovsky
2206.02963	Improving Knowledge Graph Embedding via Iterative Self-Semantic Knowledge Distillation	Machine Learning (cs.LG)	Zhehui Zhou, Defang Chen, Can Wang, Yan Feng, Chun Chen
2206.02976	Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm	Machine Learning (cs.LG)	Aidan Good, Jiaqi Lin, Hannah Sieg, Mikey Ferguson, Xin Yu, Shandian Zhe, Jerzy Wieczorek, Thiago Serra
2206.02999	DiMS: Distilling Multiple Steps of Iterative Non-Autoregressive Transformers	Computation and Language (cs.CL)	Sajad Norouzi, Rasa Hosseinzadeh, Felipe Perez, Maksims Volkovs
2206.03354	cViL: Cross-Lingual Training of Vision-Language Models using Knowledge Distillation	Computation and Language (cs.CL)	Kshitij Gupta, Devansh Gautam, Radhika Mamidi
2206.03367	Localizing Semantic Patches for Accelerating Image Classification	Computer Vision and Pattern Recognition (cs.CV)	Chuanguang Yang, Zhulin An, Yongjun Xu
2206.03410	Fast and Robust Non-Rigid Registration Using Accelerated Majorization-Minimization	Computer Vision and Pattern Recognition (cs.CV)	Yuxin Yao, Bailin Deng, Weiwei Xu, Juyong Zhang
2206.03588	Distributed Newton-Type Methods with Communication Compression and Bernoulli Aggregation	Machine Learning (cs.LG)	Rustem Islamov, Xun Qian, Slavomír Hanzely, Mher Safaryan, Peter Richtárik
2206.03596	Neural Network Compression via Effective Filter Analysis and Hierarchical Pruning	Machine Learning (cs.LG)	Ziqi Zhou, Li Lian, Yilong Yin, Ze Wang
2206.03665	Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression	Machine Learning (cs.LG)	Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan
2206.03970	Narrowing the Coordinate-frame Gap in Behavior Prediction Models: Distillation for Efficient and Accurate Scene-centric Motion Forecasting	Computer Vision and Pattern Recognition (cs.CV)	DiJia Su, Bertrand Douillard, Rami Al-Rfou, Cheolho Park, Benjamin Sapp
2206.04029	Accelerating Score-based Generative Models for High-Resolution Image Synthesis	Computer Vision and Pattern Recognition (cs.CV)	Hengyuan Ma, Li Zhang, Xiatian Zhu, Jingfeng Zhang, Jianfeng Feng
2206.04385	HideNseek: Federated Lottery Ticket via Server-side Pruning and Sign Supermask	Machine Learning (cs.LG)	Anish K. Vallapuram, Pengyuan Zhou, Young D. Kwon, Lik Hang Lee, Hengwei Xu, Pan Hui
2206.04459	SDQ: Stochastic Differentiable Quantization with Mixed Precision	Machine Learning (cs.LG)	Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric Xing, Kwang-Ting Cheng
2206.04662	DiSparse: Disentangled Sparsification for Multitask Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Xinglong Sun, Ali Hassani, Zhangyang Wang, Gao Huang, Humphrey Shi
2206.04746	HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration	Machine Learning (cs.LG)	William Andrew Simon, Una Pale, Tomas Teijeiro, David Atienza
2206.04832	Transformer-Graph Neural Network with Global-Local Attention for Multimodal Rumour Detection with Knowledge Distillation	Multimedia (cs.MM)	Tsun-hin Cheung, Kin-man Lam
2206.05459	NPU-Accelerated Imitation Learning for Thermal Optimization of QoS-Constrained Heterogeneous Multi-Cores	Distributed, Parallel, and Cluster Computing (cs.DC)	Martin Rapp, Heba Khdr, Nikita Krohmer, Jörg Henkel
2206.05475	Reducing Capacity Gap in Knowledge Distillation with Review Mechanism for Crowd Counting	Machine Learning (cs.LG)	Yunxin Liu, Qiaosi Yi, Jinshan Zeng
2206.05598	Convex Quantization Preserves Logconcavity	Signal Processing (eess.SP)	Pol del Aguila Pla, Aleix Boquet-Pujadas, Joakim Jaldén
2206.05604	A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation	Machine Learning (stat.ML)	Wenjing Yang, Ganghua Wang, Enmao Diao, Vahid Tarokh, Jie Ding, Yuhong Yang
2206.05703	PAC-Net: A Model Pruning Approach to Inductive Transfer Learning	Machine Learning (cs.LG)	Sanghoon Myung, In Huh, Wonik Jang, Jae Myung Choe, Jisu Ryu, Dae Sin Kim, Kee-Eung Kim, Changwook Jeong
2206.05846	InBiaseD: Inductive Bias Distillation to Improve Generalization and Robustness through Shape-awareness	Computer Vision and Pattern Recognition (cs.CV)	Shruthi Gowda, Bahram Zonooz, Elahe Arani
2206.05859	A Directed-Evolution Method for Sparsification and Compression of Neural Networks with Application to Object Identification and Segmentation and considerations of optimal quantization using small number of bits	Machine Learning (cs.LG)	Luiz M Franca-Neto
2206.05891	Accelerating Federated Learning via Sampling Anchor Clients with Large Batches	Machine Learning (cs.LG)	Feijie Wu, Song Guo, Zhihao Qu, Shiqi He, Ziming Liu
2206.05916	Why Quantization Improves Generalization: NTK of Binary Weight Neural Networks	Machine Learning (cs.LG)	Kaiqi Zhang, Ming Yin, Yu-Xiang Wang
2206.05974	Deep Neural Network Based Accelerated Failure Time Models using Rank Loss	Machine Learning (stat.ML)	Gwangsu Kim, Sangwook Kang
2206.05998	GPU-Accelerated Machine Learning in Non-Orthogonal Multiple Access	Signal Processing (eess.SP)	Daniel Schäufele, Guillermo Marcus, Nikolaus Binder, Matthias Mehlhose, Alexander Keller, Sławomir Stańczak
2206.06067	Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Zengyu Qiu, Xinzhu Ma, Kunlin Yang, Chunya Liu, Jun Hou, Shuai Yi, Wanli Ouyang
2206.06217	Towards an Approximation-Aware Computational Workflow Framework for Accelerating Large-Scale Discovery Tasks	Distributed, Parallel, and Cluster Computing (cs.DC)	Michael A. Johnston, Vassilis Vassiliadis
2206.06247	Leveraging Structured Pruning of Convolutional Neural Networks	Neural and Evolutionary Computing (cs.NE)	Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, David Bertrand, Thomas Hannagan
2206.06255	Energy Consumption Analysis of pruned Semantic Segmentation Networks on an Embedded GPU	Neural and Evolutionary Computing (cs.NE)	Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, David Bertrand, Thomas Hannagan
2206.06479	Robust Distillation for Worst-class Performance	Machine Learning (cs.LG)	Serena Wang, Harikrishna Narasimhan, Yichen Zhou, Sara Hooker, Michal Lukasik, Aditya Krishna Menon
2206.06487	The Modality Focusing Hypothesis: On the Blink of Multimodal Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Zihui Xue, Zhengqi Gao, Sucheng Ren, Hang Zhao
2206.06501	Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training	Machine Learning (cs.LG)	Charbel Sakr, Steve Dai, Rangharajan Venkatesan, Brian Zimmer, William J. Dally, Brucek Khailany
2206.06561	FreeKD: Free-direction Knowledge Distillation for Graph Neural Networks	Machine Learning (cs.LG)	Kaituo Feng, Changsheng Li, Ye Yuan, Guoren Wang
2206.06563	Zeroth-Order Topological Insights into Iterative Magnitude Pruning	Machine Learning (cs.LG)	Aishwarya Balwani, Jakob Krzyston
2206.06611	Accelerating CPU-Based Sparse General Matrix Multiplication With Binary Row Merging	Distributed, Parallel, and Cluster Computing (cs.DC)	Zhaoyang Du, Yijin Guan, Tianchan Guan, Dimin Niu, Hongzhong Zheng, Yuan Xie
2206.06661	SoTeacher: A Student-oriented Teacher Network Training Framework for Knowledge Distillation	Machine Learning (cs.LG)	Chengyu Dong, Liyuan Liu, Jingbo Shang
2206.07021	Federated Optimization Algorithms with Random Reshuffling and Gradient Compression	Machine Learning (cs.LG)	Abdurakhmon Sadiev, Grigory Malinovsky, Eduard Gorbunov, Igor Sokolov, Ahmed Khaled, Konstantin Burlachenko, Peter Richtárik
2206.07307	VCT: A Video Compression Transformer	Computer Vision and Pattern Recognition (cs.CV)	Fabian Mentzer, George Toderici, David Minnen, Sung-Jin Hwang, Sergi Caelles, Mario Lucic, Eirikur Agustsson
2206.07311	Can pruning improve certified robustness of neural networks?	Machine Learning (cs.LG)	Zhangheng Li, Tianlong Chen, Linyi Li, Bo Li, Zhangyang Wang
2206.07406	Hardening DNNs against Transfer Attacks during Network Compression using Greedy Adversarial Pruning	Machine Learning (cs.LG)	Jonah O'Brien Weiss, Tiago Alves, Sandip Kundu
2206.07562	Bayesian Federated Learning via Predictive Distribution Distillation	Machine Learning (cs.LG)	Shrey Bhatt, Aishwarya Gupta, Piyush Rai
2206.07649	Atrial Fibrillation Detection Using Weight-Pruned, Log-Quantised Convolutional Neural Networks	Signal Processing (eess.SP)	Xiu Qi Chang, Ann Feng Chew, Benjamin Chen Ming Choong, Shuhui Wang, Rui Han, Wang He, Li Xiaolin, Rajesh C. Panicker, Deepu John
2206.07673	Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling	Machine Learning (stat.ML)	Jiri Hron, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein
2206.07681	Learning to Accelerate Partial Differential Equations via Latent Global Evolution	Machine Learning (cs.LG)	Tailin Wu, Takashi Maruyama, Jure Leskovec
2206.07808	Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems	Computation and Language (cs.CL)	Jack FitzGerald, Shankar Ananthakrishnan, Konstantine Arkoudas, Davide Bernardi, Abhishek Bhagia, Claudio Delli Bovi, Jin Cao, Rakesh Chada, Amit Chauhan, Luoxin Chen, Anurag Dwarakanath, Satyam Dwivedi, Turan Gojayev, Karthik Gopalakrishnan, Thomas Gueudre, Dilek Hakkani-Tur, Wael Hamza, Jonathan Hueser, Kevin Martin Jose, Haidar Khan, Beiye Liu, Jianhua Lu, Alessandro Manzotti, Pradeep Natarajan, Karolina Owczarzak, Gokmen Oz, Enrico Palumbo, Charith Peris, Chandana Satya Prakash, Stephen Rawls, Andy Rosenbaum, Anjali Shenoy, Saleh Soltan, Mukund Harakere Sridhar, Liz Tan, Fabian Triefenbach, Pan Wei, Haiyang Yu, Shuai Zheng, Gokhan Tur, Prem Natarajan
2206.07839	Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness	Machine Learning (cs.LG)	Tianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu, Pin-Yu Chen, Zhangyang Wang
2206.07882	Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization	Computation and Language (cs.CL)	Andrea Fasoli, Chia-Yu Chen, Mauricio Serrano, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Kailash Gopalakrishnan
2206.07904	Explainable Models via Compression of Tree Ensembles	Machine Learning (cs.LG)	Siwen Yan, Sriraam Natarajan, Saket Joshi, Roni Khardon, Prasad Tadepalli
2206.08014	On Error and Compression Rates for Prototype Rules	Machine Learning (cs.LG)	Omer Kerem, Roi Weiss
2206.08152	Fault-Tolerant Collaborative Inference through the Edge-PRUNE Framework	Machine Learning (cs.LG)	Jani Boutellier, Bo Tan, Jari Nurmi
2206.08186	Asymptotic Soft Cluster Pruning for Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Tao Niu, Yinglei Teng, Panpan Zou
2206.08224	Multi scale Feature Extraction and Fusion for Online Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Panpan Zou, Yinglei Teng, Tao Niu
2206.08491	Revisiting Self-Distillation	Machine Learning (cs.LG)	Minh Pham, Minsu Cho, Ameya Joshi, Chinmay Hegde
2206.08516	MetaFed: Federated Learning among Federations with Cyclic Knowledge Distillation for Personalized Healthcare	Machine Learning (cs.LG)	Yiqiang Chen, Wang Lu, Xin Qin, Jindong Wang, Xing Xie
2206.08529	Accelerating Shapley Explanation via Contributive Cooperator Selection	Machine Learning (cs.LG)	Guanchu Wang, Yu-Neng Chuang, Mengnan Du, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Hu
2206.08684	Sparse Double Descent: Where Network Pruning Aggravates Overfitting	Machine Learning (cs.LG)	Zheng He, Zeke Xie, Quanzhi Zhu, Zengchang Qin
2206.08869	Fast Lossless Neural Compression with Integer-Only Discrete Flows	Machine Learning (cs.LG)	Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang
2206.08880	Improving Generalization of Metric Learning via Listwise Self-distillation	Computer Vision and Pattern Recognition (cs.CV)	Zelong Zeng, Fan Yang, Zheng Wang, Shin'ichi Satoh
2206.08889	Lossy Compression with Gaussian Diffusion	Machine Learning (stat.ML)	Lucas Theis, Tim Salimans, Matthew D. Hoffman, Fabian Mentzer
2206.09548	Variational Distillation for Multi-View Learning	Computer Vision and Pattern Recognition (cs.CV)	Xudong Tian, Zhizhong Zhang, Cong Wang, Wensheng Zhang, Yanyun Qu, Lizhuang Ma, Zongze Wu, Yuan Xie, Dacheng Tao
2206.09604	Distortion-Aware Network Pruning and Feature Reuse for Real-time Video Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Hyunsu Rhee, Dongchan Min, Sunil Hwang, Bruno Andreis, Sung Ju Hwang
2206.09796	Knowledge Distillation for Oriented Object Detection on Aerial Images	Computer Vision and Pattern Recognition (cs.CV)	Yicheng Xiao, Junpeng Zhang
2206.09806	Self-Supervised Consistent Quantization for Fully Unsupervised Image Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Guile Wu, Chao Zhang, Stephan Liwicki
2206.09888	SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression	Machine Learning (cs.LG)	Zhize Li, Haoyu Zhao, Boyue Li, Yuejie Chi
2206.10082	Optimally Controllable Perceptual Lossy Compression	Computer Vision and Pattern Recognition (cs.CV)	Zeyu Yan, Fei Wen, Peilin Liu
2206.10088	Renormalized Sparse Neural Network Pruning	Machine Learning (cs.LG)	Michael G. Rawson
2206.10131	An Integrated Representation & Compression Scheme Based on Convolutional Autoencoders with 4D DCT Perceptual Encoding for High Dynamic Range Light Fields	Computer Vision and Pattern Recognition (cs.CV)	Sally Khaidem, Mansi Sharma
2206.10451	Winning the Lottery Ahead of Time: Efficient Early Network Pruning	Machine Learning (cs.LG)	John Rachwan, Daniel Zügner, Bertrand Charpentier, Simon Geisler, Morgane Ayle, Stephan Günnemann
2206.10452	Shifted Compression Framework: Generalizations and Improvements	Machine Learning (cs.LG)	Egor Shulgin, Peter Richtárik
2206.10461	An Automatic and Efficient BERT Pruning for Edge AI Systems	Computation and Language (cs.CL)	Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding
2206.10526	QuantFace: Towards Lightweight Face Recognition by Synthetic Data Low-bit Quantization	Computer Vision and Pattern Recognition (cs.CV)	Fadi Boutros, Naser Damer, Arjan Kuijper
2206.10801	Automated Cancer Subtyping via Vector Quantization Mutual Information Maximization	Machine Learning (cs.LG)	Zheng Chen, Lingwei Zhu, Ziwei Yang, Takashi Matsubara
2206.10844	Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices	Machine Learning (cs.LG)	Kartik Gupta, Marios Fournarakis, Matthias Reisser, Christos Louizos, Markus Nagel
2206.11062	Answer Fast: Accelerating BERT on the Tensor Streaming Processor	Machine Learning (cs.LG)	Ibrahim Ahmed, Sahil Parmar, Matthew Boyd, Michael Beidler, Kris Kang, Bill Liu, Kyle Roach, John Kim, Dennis Abts
2206.11297	ROIBIN-SZ: Fast and Science-Preserving Compression for Serial Crystallography	Distributed, Parallel, and Cluster Computing (cs.DC)	Robert Underwood, Chun Yoon, Ali Gok, Sheng Di, Franck Cappello
2206.11556	A Federated Reinforcement Learning Method with Quantization for Cooperative Edge Caching in Fog Radio Access Networks	Signal Processing (eess.SP)	Yanxiang Jiang, Min Zhang, Fu-Chun Zheng, Yan Chen, Mehdi Bennis, Xiaohu You
2206.12005	Knowledge Distillation via Weighted Ensemble of Teaching Assistants	Machine Learning (cs.LG)	Durga Prasad Ganta, Himel Das Gupta, Victor S. Sheng
2206.12370	Online Distillation with Mixed Sample Augmentation	Computer Vision and Pattern Recognition (cs.CV)	Yiqing Shen, Liwu Xu, Yuzhe Yang, Yaqian Li, Yandong Guo
2206.12372	QReg: On Regularization Effects of Quantization	Computer Vision and Pattern Recognition (cs.CV)	MohammadHossein AskariHemmat, Reyhane Askari Hemmat, Alex Hoffman, Ivan Lazarevich, Ehsan Saboori, Olivier Mastropietro, Sudhakar Sah, Yvon Savaria, Jean-Pierre David
2206.12562	PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance	Machine Learning (cs.LG)	Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao
2206.12638	Distilling a Pretrained Language Model to a Multilingual ASR Model	Computation and Language (cs.CL)	Kwanghee Choi, Hyung-Min Park
2206.12788	Knowledge Distillation with Representative Teacher Keys Based on Attention Mechanism for Image Classification Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Jun-Teng Yang, Sheng-Che Kao, Scott C.-H. Huang
2206.12794	CTMQ: Cyclic Training of Convolutional Neural Networks with Multiple Quantization Steps	Computer Vision and Pattern Recognition (cs.CV)	HyunJin Kim, Jungwoo Shin, Alberto A. Del Barrio
2206.13130	Revisiting Architecture-aware Knowledge Distillation: Smaller Models and Faster Search	Machine Learning (cs.LG)	Taehyeon Kim, Heesoo Myeong, Se-Young Yun
2206.13140	Compressing Features for Learning with Noisy Labels	Machine Learning (cs.LG)	Yingyi Chen, Shell Xu Hu, Xi Shen, Chunrong Ai, Johan A.K. Suykens
2206.13214	Few-Shot Stance Detection via Target-Aware Prompt Distillation	Computation and Language (cs.CL)	Yan Jiang, Jinhua Gao, Huawei Shen, Xueqi Cheng
2206.13236	Pruned RNN-T for fast, memory-efficient ASR training	Audio and Speech Processing (eess.AS)	Fangjun Kuang, Liyong Guo, Wei Kang, Long Lin, Mingshuang Luo, Zengwei Yao, Daniel Povey
2206.14056	Deep Neural Networks pruning via the Structured Perspective Regularization	Machine Learning (cs.LG)	Matteo Cacciola, Antonio Frangioni, Xinlin Li, Andrea Lodi
2206.14366	Knowledge Distillation of Transformer-based Language Models Revisited	Computation and Language (cs.CL)	Chengqiang Lu, Jianwei Zhang, Yunfei Chu, Zhengyu Chen, Jingren Zhou, Fei Wu, Haiqing Chen, Hongxia Yang
2206.14413	The Lighter The Better: Rethinking Transformers in Medical Image Segmentation Through Adaptive Pruning	Computer Vision and Pattern Recognition (cs.CV)	Xian Lin, Li Yu, Kwang-Ting Cheng, Zengqiang Yan
2206.14464	SPI-GAN: Distilling Score-based Generative Models with Straight-Path Interpolations	Machine Learning (cs.LG)	Jinsung Jeon, Noseong Park
2206.14486	Beyond neural scaling laws: beating power law scaling via data pruning	Machine Learning (cs.LG)	Ben Sorscher, Robert Geirhos, Shashank Shekhar, Surya Ganguli, Ari S. Morcos
2206.14532	Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing?	Machine Learning (cs.LG)	Keshigeyan Chandrasegaran, Ngoc-Trung Tran, Yunqing Zhao, Ngai-Man Cheung
2206.14658	Cut Inner Layers: A Structured Pruning Strategy for Efficient U-Net GANs	Machine Learning (cs.LG)	Bo-Kyeong Kim, Shinkook Choi, Hancheol Park
2206.14754	Distilling Model Failures as Directions in Latent Space	Machine Learning (cs.LG)	Saachi Jain, Hannah Lawrence, Ankur Moitra, Aleksander Madry
2206.14761	Accelerating Parallel Write via Deeply Integrating Predictive Lossy Compression with HDF5	Distributed, Parallel, and Cluster Computing (cs.DC)	Sian Jin, Dingwen Tao, Houjun Tang, Sheng Di, Suren Byna, Zarija Lukic, Franck Cappello
2206.15014	Compressing Pre-trained Transformers via Low-Bit NxM Sparsity for Natural Language Understanding	Computation and Language (cs.CL)	Connor Holmes, Minjia Zhang, Yuxiong He, Bo Wu
2206.15047	Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation	Machine Learning (cs.LG)	Giung Nam, Hyungi Lee, Byeongho Heo, Juho Lee
2207.00112	Language model compression with weighted low-rank factorization	Machine Learning (cs.LG)	Yen-Chang Hsu, Ting Hua, Sungen Chang, Qian Lou, Yilin Shen, Hongxia Jin
2207.00200	Studying the impact of magnitude pruning on contrastive learning methods	Machine Learning (cs.LG)	Francesco Corti, Rahim Entezari, Sara Hooker, Davide Bacciu, Olga Saukh
2207.00392	Better Methods and Theory for Federated Learning: Compression, Client Selection and Heterogeneity	Machine Learning (cs.LG)	Samuel Horváth
2207.00555	FitHuBERT: Going Thinner and Deeper for Knowledge Distillation of Speech Self-Supervised Learning	Audio and Speech Processing (eess.AS)	Yeonghyeon Lee, Kangwook Jang, Jahyun Goo, Youngmoon Jung, Hoirin Kim
2207.00586	PrUE: Distilling Knowledge from Sparse Teacher Networks	Computer Vision and Pattern Recognition (cs.CV)	Shaopu Wang, Xiaojun Chen, Mengzhen Kou, Jinqiao Shi
2207.00611	FAIR principles for AI models, with a practical application for accelerated high energy diffraction microscopy	Artificial Intelligence (cs.AI)	Nikil Ravi, Pranshu Chaturvedi, E. A. Huerta, Zhengchun Liu, Ryan Chard, Aristana Scourtas, K.J. Schmidt, Kyle Chard, Ben Blaiszik, Ian Foster
2207.00694	Efficient Adversarial Training With Data Pruning	Machine Learning (cs.LG)	Maximilian Kaufmann, Yiren Zhao, Ilia Shumailov, Robert Mullins, Nicolas Papernot
2207.01260	CPrune: Compiler-Informed Model Pruning for Efficient Target-Aware DNN Execution	Machine Learning (cs.LG)	Taeho Kim, Yongin Kwon, Jemin Lee, Taeho Kim, Sangtae Ha
2207.01394	BiTAT: Neural Network Binarization with Task-dependent Aggregated Transformation	Computer Vision and Pattern Recognition (cs.CV)	Geon Park, Jaehong Yoon, Haiyang Zhang, Xing Zhang, Sung Ju Hwang, Yonina C. Eldar
2207.01405	I-ViT: Integer-only Quantization for Efficient Vision Transformer Inference	Computer Vision and Pattern Recognition (cs.CV)	Zhikai Li, Qingyi Gu
2207.01411	The Neural-Prediction based Acceleration Algorithm of Column Generation for Graph-Based Set Covering Problems	Machine Learning (cs.LG)	Haofeng Yuan, Peng Jiang, Shiji Song
2207.01426	Dynamic Contrastive Distillation for Image-Text Retrieval	Multimedia (cs.MM)	Jun Rao, Liang Ding, Shuhan Qi, Meng Fang, Yang Liu, Li Shen, Dacheng Tao
2207.01768	Rank-Based Filter Pruning for Real-Time UAV Tracking	Computer Vision and Pattern Recognition (cs.CV)	Xucheng Wang, Dan Zeng, Qijun Zhao, Shuiwang Li
2207.01908	Pushing the Limit of Phase Shift Feedback Compression for Intelligent Reflecting Surface-Assisted Wireless Systems by Exploiting Global Attention	Signal Processing (eess.SP)	Xianhua Yu, Dong Li
2207.02039	PKD: General Distillation Framework for Object Detectors via Pearson Correlation Coefficient	Computer Vision and Pattern Recognition (cs.CV)	Weihan Cao, Yifan Zhang, Jianfei Gao, Anda Cheng, Ke Cheng, Jian Cheng
2207.02189	Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time	Machine Learning (cs.LG)	Jun-Kun Wang, Andre Wibisono
2207.02196	Accelerating Score-based Generative Models with Preconditioned Diffusion Sampling	Computer Vision and Pattern Recognition (cs.CV)	Hengyuan Ma, Li Zhang, Xiatian Zhu, Jianfeng Feng
2207.02437	Complementary Bi-directional Feature Compression for Indoor 360° Semantic Segmentation with Self-distillation	Computer Vision and Pattern Recognition (cs.CV)	Zishuo Zheng, Chunyu Lin, Lang Nie, Kang Liao, Zhijie Shen, Yao Zhao
2207.02445	Distillation to Enhance the Portability of Risk Models Across Institutions with Large Patient Claims Database	Machine Learning (cs.LG)	Steve Nyemba, Chao Yan, Ziqi Zhang, Amol Rajmane, Pablo Meyer, Prithwish Chakraborty, Bradley Malin
2207.02449	Information Compression and Performance Evaluation of Tic-Tac-Toe's Evaluation Function Using Singular Value Decomposition	Machine Learning (cs.LG)	Naoya Fujita, Hiroshi Watanabe
2207.02463	Gender Biases and Where to Find Them: Exploring Gender Bias in Pre-Trained Transformer-based Language Models Using Movement Pruning	Computation and Language (cs.CL)	Przemyslaw Joniak, Akiko Aizawa
2207.02632	Network Pruning via Feature Shift Minimization	Computer Vision and Pattern Recognition (cs.CV)	Yuanzhi Duan, Xiaofang Hu, Yue Zhou, Peng He, Qiang Liu, Shukai Duan
2207.02970	Network Binarization via Contrastive Learning	Computer Vision and Pattern Recognition (cs.CV)	Yuzhang Shang, Dan Xu, Ziliang Zong, Liqiang Nie, Yan Yan
2207.03088	Attention Round for Post-Training Quantization	Machine Learning (cs.LG)	Huabin Diao, Gongyan Li, Shaoyun Xu, Yuexing Hao
2207.03128	PointMCD: Boosting Deep Point Cloud Encoders via Multi-view Cross-modal Distillation for 3D Shape Recognition	Computer Vision and Pattern Recognition (cs.CV)	Qijian Zhang, Junhui Hou, Yue Qian
2207.03331	Low-resource Low-footprint Wake-word Detection using Knowledge Distillation	Audio and Speech Processing (eess.AS)	Arindam Ghosh, Mark Fuhs, Deblin Bagchi, Bahman Farahani, Monika Woszczyna
2207.03334	Speech Emotion: Investigating Model Representations, Multi-Task Learning and Knowledge Distillation	Audio and Speech Processing (eess.AS)	Vikramjit Mitra, Hsiang-Yun Sherry Chien, Vasudha Kowtha, Joseph Yitan Cheng, Erdrin Azemi
2207.03335	Distilling Ensemble of Explanations for Weakly-Supervised Pre-Training of Image Segmentation Models	Computer Vision and Pattern Recognition (cs.CV)	Xuhong Li, Haoyi Xiong, Yi Liu, Dingfu Zhou, Zeyu Chen, Yaqing Wang, Dejing Dou
2207.03638	A Support Vector Model of Pruning Trees Evaluation Based on OTSU Algorithm	Computer Vision and Pattern Recognition (cs.CV)	Yuefei Chen, Xinli Zheng, Chunhua Ju, Fuguang Bao
2207.03644	Pruning Early Exit Networks	Machine Learning (cs.LG)	Alperen Görmez, Erdem Koyuncu
2207.03677	SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning	Computer Vision and Pattern Recognition (cs.CV)	Haoran You, Baopu Li, Zhanyi Sun, Xu Ouyang, Yingyan Lin
2207.03758	Virtual Axle Detector based on Analysis of Bridge Acceleration Measurements by Fully Convolutional Network	Computer Vision and Pattern Recognition (cs.CV)	Steven Robert Lorenzen, Henrik Riedel, Maximilian Michael Rupp, Leon Schmeiser, Hagen Berthold, Andrei Firus, Jens Schneider
2207.03957	Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with Inexact Prox	Machine Learning (cs.LG)	Abdurakhmon Sadiev, Dmitry Kovalev, Peter Richtárik
2207.04144	L$_0$onie: Compressing COINs with L$_0$-constraints	Machine Learning (cs.LG)	Juan Ramirez, Jose Gallego-Posada
2207.04231	CEG4N: Counter-Example Guided Neural Network Quantization Refinement	Machine Learning (cs.LG)	João Batista P. Matos Jr., Iury Bessa, Edoardo Manino, Xidan Song, Lucas C. Cordeiro
2207.04546	FairDistillation: Mitigating Stereotyping in Language Models	Computation and Language (cs.CL)	Pieter Delobelle, Bettina Berendt
2207.05049	Fast-Vid2Vid: Spatial-Temporal Compression for Video-to-Video Synthesis	Computer Vision and Pattern Recognition (cs.CV)	Long Zhuo, Guangcong Wang, Shikai Li, Wayne Wu, Ziwei Liu
2207.05256	Normalized Feature Distillation for Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Tao Liu, Xi Yang, Chenshu Chen
2207.05273	Cross-Architecture Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yufan Liu, Jiajiong Cao, Bing Li, Weiming Hu, Jingting Ding, Liang Li
2207.05315	CANF-VC: Conditional Augmented Normalizing Flows for Video Compression	Computer Vision and Pattern Recognition (cs.CV)	Yung-Han Ho, Chih-Peng Chang, Peng-Yu Chen, Alessandro Gnutti, Wen-Hsiao Peng
2207.05345	HEAD: HEtero-Assists Distillation for Heterogeneous Object Detectors	Computer Vision and Pattern Recognition (cs.CV)	Luting Wang, Xiaojie Li, Yue Liao, Zeren Jiang, Jianlong Wu, Fei Wang, Chen Qian, Si Liu
2207.05409	Knowledge Condensation Distillation	Computer Vision and Pattern Recognition (cs.CV)	Chenxin Li, Mingbao Lin, Zhiyuan Ding, Nie Lin, Yihong Zhuang, Yue Huang, Xinghao Ding, Liujuan Cao
2207.05432	Synergistic Self-supervised and Quantization Learning	Computer Vision and Pattern Recognition (cs.CV)	Yun-Hao Cao, Peiqin Sun, Yechang Huang, Jianxin Wu, Shuchang Zhou
2207.05497	Paint and Distill: Boosting 3D Object Detection with Semantic Passing Network	Computer Vision and Pattern Recognition (cs.CV)	Bo Ju, Zhikang Zou, Xiaoqing Ye, Minyue Jiang, Xiao Tan, Errui Ding, Jingdong Wang
2207.05500	Modality-Aware Contrastive Instance Learning with Self-Distillation for Weakly-Supervised Audio-Visual Violence Detection	Computer Vision and Pattern Recognition (cs.CV)	Jiashuo Yu, Jinyu Liu, Ying Cheng, Rui Feng, Yuejie Zhang
2207.05692	Lip-Listening: Mixing Senses to Understand Lips using Cross Modality Knowledge Distillation for Word-Based Models	Multimedia (cs.MM)	Hadeel Mabrouk, Omar Abugabal, Nourhan Sakr, Hesham M. Eraqi
2207.06282	DiverGet: A Search-Based Software Testing Approach for Deep Neural Network Quantization Assessment	Machine Learning (cs.LG)	Ahmed Haj Yahmed, Houssem Ben Braiek, Foutse Khomh, Sonia Bouzidi, Rania Zaatour
2207.06646	DropNet: Reducing Neural Network Complexity via Iterative Pruning	Machine Learning (cs.LG)	John Tan Chong Min, Mehul Motani
2207.06667	Large-scale Knowledge Distillation with Elastic Heterogeneous Computing Resources	Distributed, Parallel, and Cluster Computing (cs.DC)	Ji Liu, Daxiang Dong, Xi Wang, An Qin, Xingjian Li, Patrick Valduriez, Dejing Dou, Dianhai Yu
2207.06694	Dynamic Low-Resolution Distillation for Cost-Efficient End-to-End Text Spotting	Computer Vision and Pattern Recognition (cs.CV)	Ying Chen, Liang Qiao, Zhanzhan Cheng, Shiliang Pu, Yi Niu, Xi Li
2207.06738	Semi-supervised Vector-Quantization in Visual SLAM using HGCN	Computer Vision and Pattern Recognition (cs.CV)	Amir Zarringhalam (1), Saeed Shiry Ghidary (2), Ali Mohades Khorasani (3) ((1),(2) and (3), Amirkabir University of Technology)
2207.06825	Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions	Computer Vision and Pattern Recognition (cs.CV)	David Bruggemann, Christos Sakaridis, Prune Truong, Luc Van Gool
2207.06867	Deep versus Wide: An Analysis of Student Architectures for Task-Agnostic Knowledge Distillation of Self-Supervised Speech Models	Computation and Language (cs.CL)	Takanori Ashihara, Takafumi Moriya, Kohei Matsuura, Tomohiro Tanaka
2207.06924	Learning Representations for CSI Adaptive Quantization and Feedback	Signal Processing (eess.SP)	Valentina Rizzello, Matteo Nerini, Michael Joham, Bruno Clerckx, Wolfgang Utschick
2207.06968	PR-DARTS: Pruning-Based Differentiable Architecture Search	Computer Vision and Pattern Recognition (cs.CV)	Hamid Mousavi, Mohammad Loni, Mina Alibeigi, Masoud Daneshtalab
2207.07223	Accelerated Federated Learning with Decoupled Adaptive Optimization	Machine Learning (cs.LG)	Jiayin Jin, Jiaxiang Ren, Yang Zhou, Lingjuan Lyu, Ji Liu, Dejing Dou
2207.07260	Accelerated Probabilistic Marching Cubes by Deep Learning for Time-Varying Scalar Ensembles	Machine Learning (cs.LG)	Mengjiao Han, Tushar M. Athawale, David Pugmire, Chris R. Johnson
2207.07958	FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning	Machine Learning (cs.LG)	Javier Duarte, Nhan Tran, Ben Hawks, Christian Herwig, Jules Muhizi, Shvetank Prakash, Vijay Janapa Reddi
2207.08063	Subclass Knowledge Distillation with Known Subclass Labels	Machine Learning (cs.LG)	Ahmad Sajedi, Yuri A. Lawryshyn, Konstantinos N. Plataniotis
2207.08096	Nonmyopic Distilled Data Association Belief Space Planning Under Budget Constraints	Artificial Intelligence (cs.AI)	Moshe Shienman, Vadim Indelman
2207.08181	Federated Continual Learning through distillation in pervasive computing	Machine Learning (cs.LG)	Anastasiia Usmanova, François Portet, Philippe Lalanda, German Vega
2207.08338	MobileCodec: Neural Inter-frame Video Compression on Mobile Devices	Computer Vision and Pattern Recognition (cs.CV)	Hoang Le, Liang Zhang, Amir Said, Guillaume Sautiere, Yang Yang, Pranav Shrestha, Fei Yin, Reza Pourreza, Auke Wiggers
2207.08356	Learning Knowledge Representation with Meta Knowledge Distillation for Single Image Super-Resolution	Computer Vision and Pattern Recognition (cs.CV)	Han Zhu, Zhenzhong Chen, Shan Liu
2207.08629	Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks	Machine Learning (cs.LG)	Chuang Liu, Xueqi Ma, Yibing Zhan, Liang Ding, Dapeng Tao, Bo Du, Wenbin Hu, Danilo Mandic
2207.08820	Accelerating Deep Learning Model Inference on Arm CPUs with Ultra-Low Bit Quantization and Runtime	Machine Learning (cs.LG)	Saad Ashfaq, MohammadHossein AskariHemmat, Sudhakar Sah, Ehsan Saboori, Olivier Mastropietro, Alexander Hoffman
2207.09070	Context Unaware Knowledge Distillation for Image Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Bytasandram Yaswanth Reddy, Shiv Ram Dubey, Rakesh Kumar Sanodiya, Ravi Ranjan Prasad Karn
2207.09158	FedX: Unsupervised Federated Learning with Cross Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Sungwon Han, Sungwon Park, Fangzhao Wu, Sundong Kim, Chuhan Wu, Xing Xie, Meeyoung Cha
2207.09408	Bounding generalization error with input compression: An empirical study with infinite-width networks	Machine Learning (cs.LG)	Angus Galloway, Anna Golubeva, Mahmoud Salem, Mihai Nica, Yani Ioannou, Graham W. Taylor
2207.09530	Knowledge distillation with a class-aware loss for endoscopic disease detection	Computer Vision and Pattern Recognition (cs.CV)	Pedro E. Chavarrias-Solanon, Mansoor Ali-Teevno, Gilberto Ochoa-Ruiz, Sharib Ali
2207.10082	Model Compression for Resource-Constrained Mobile Robots	Machine Learning (cs.LG)	Timotheos Souroulla (Ericsson Research AI), Alberto Hata (Ericsson Research AI), Ahmad Terra (Ericsson Research AI), Özer Özkahraman (KTH, Royal Institute of Technology), Rafia Inam (Ericsson Research AI)
2207.10083	Mixed-Precision Inference Quantization: Radically Towards Faster inference speed, Lower Storage requirement, and Lower Loss	Machine Learning (cs.LG)	Daning Cheng, Wenguang Chen
2207.10188	Bitwidth-Adaptive Quantization-Aware Neural Network Training: A Meta-Learning Approach	Machine Learning (cs.LG)	Jiseok Youn, Jaehun Song, Hyung-Sin Kim, Saewoong Bahk
2207.10345	CADyQ: Content-Aware Dynamic Quantization for Image Super-Resolution	Computer Vision and Pattern Recognition (cs.CV)	Cheeun Hong, Sungyong Baik, Heewon Kim, Seungjun Nah, Kyoung Mu Lee
2207.10425	KD-MVS: Knowledge Distillation Based Self-supervised Learning for MVS	Computer Vision and Pattern Recognition (cs.CV)	Yikang Ding, Qingtian Zhu, Xiangyue Liu, Wentao Yuan, Haotian Zhang, CHi Zhang
2207.10666	TinyViT: Fast Pretraining Distillation for Small Vision Transformers	Computer Vision and Pattern Recognition (cs.CV)	Kan Wu, Jinnian Zhang, Houwen Peng, Mengchen Liu, Bin Xiao, Jianlong Fu, Lu Yuan
2207.10702	Efficient model compression with Random Operation Access Specific Tile (ROAST) hashing	Machine Learning (cs.LG)	Aditya Desai, Keren Zhou, Anshumali Shrivastava
2207.10776	Auto-regressive Image Synthesis with Integrated Quantization	Computer Vision and Pattern Recognition (cs.CV)	Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Kaiwen Cui, Changgong Zhang, Shijian Lu
2207.10888	FairGRAPE: Fairness-aware GRAdient Pruning mEthod for Face Attribute Classification	Computer Vision and Pattern Recognition (cs.CV)	Xiaofeng Lin, Seungbae Kim, Jungseock Joo
2207.10969	Convergence Theory of Generalized Distributed Subgradient Method with Random Quantization	Signal Processing (eess.SP)	Zhaoyue Xia, Jun Du, Yong Ren
2207.11048	Quantized Sparse Weight Decomposition for Neural Network Compression	Machine Learning (cs.LG)	Andrey Kuzmin, Mart van Baalen, Markus Nagel, Arash Behboodi
2207.11184	Multi-Faceted Distillation of Base-Novel Commonality for Few-shot Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Shuang Wu, Wenjie Pei, Dianwen Mei, Fanglin Chen, Jiandong Tian, Guangming Lu
2207.11209	Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise Binarization	Computer Vision and Pattern Recognition (cs.CV)	Weiguang Zhao, Yuyao Yan, Chaolong Yang, Jianan Ye, Xi Yang, Kaizhu Huang
2207.11250	Rich Feature Distillation with Feature Affinity Module for Efficient Image Dehazing	Computer Vision and Pattern Recognition (cs.CV)	Sai Mitheran, Anushri Suresh, Nisha J. S., Varun P. Gopi
2207.11293	Receptive Field-based Segmentation for Distributed CNN Inference Acceleration in Collaborative Edge Computing	Distributed, Parallel, and Cluster Computing (cs.DC)	Nan Li, Alexandros Iosifidis, Qi Zhang
2207.11294	Distributed Deep Learning Inference Acceleration using Seamless Collaboration in Edge Computing	Distributed, Parallel, and Cluster Computing (cs.DC)	Nan Li, Alexandros Iosifidis, Qi Zhang
2207.11518	Online Knowledge Distillation via Mutual Contrastive Learning for Visual Recognition	Computer Vision and Pattern Recognition (cs.CV)	Chuanguang Yang, Zhulin An, Helong Zhou, Yongjun Xu, Qian Zhan
2207.11887	HIRE: Distilling High-order Relational Knowledge From Heterogeneous Graph Neural Networks	Machine Learning (cs.LG)	Jing Liu, Tongya Zheng, Qinfen Hao
2207.11906	Learning a Dual-Mode Speech Recognition Model via Self-Pruning	Audio and Speech Processing (eess.AS)	Chunxi Liu, Yuan Shangguan, Haichuan Yang, Yangyang Shi, Raghuraman Krishnamoorthi, Ozlem Kalinli
2207.12049	Few-Shot Object Detection by Knowledge Distillation Using Bag-of-Visual-Words Representations	Computer Vision and Pattern Recognition (cs.CV)	Wenjie Pei, Shuang Wu, Dianwen Mei, Fanglin Chen, Jiandong Tian, Guangming Lu
2207.12106	Black-box Few-shot Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Dang Nguyen, Sunil Gupta, Kien Do, Svetha Venkatesh
2207.12392	Self-Distilled Vision Transformer for Domain Generalization	Computer Vision and Pattern Recognition (cs.CV)	Maryam Sultana, Muzammal Naseer, Muhammad Haris Khan, Salman Khan, Fahad Shahbaz Khan
2207.12397	C3-SL: Circular Convolution-Based Batch-Wise Compression for Communication-Efficient Split Learning	Machine Learning (cs.LG)	Cheng-Yen Hsieh, Yu-Chuan Chuang, An-Yeu (Andy)Wu
2207.12534	Trainability Preserving Neural Structured Pruning	Machine Learning (cs.LG)	Huan Wang, Yun Fu
2207.12554	Inter-Frame Compression for Dynamic Point Cloud Geometry Coding	Computer Vision and Pattern Recognition (cs.CV)	Anique Akhtar, Zhu Li, Geert Van der Auwera
2207.12852	Extreme compression of sentence-transformer ranker models: faster inference, longer battery life, and less storage on edge devices	Machine Learning (cs.LG)	Amit Chaulwar, Lukas Malik, Maciej Krajewski, Felix Reichel, Leif-Nissen Lundbæk, Michael Huth, Bartlomiej Matejczyk
2207.12980	Efficient One Pass Self-distillation with Zipf's Label Smoothing	Computer Vision and Pattern Recognition (cs.CV)	Jiajun Liang, Linze Li, Zhaodong Bing, Borui Zhao, Yao Tang, Bo Lin, Haoqiang Fan
2207.13848	Predicting the Output Structure of Sparse Matrix Multiplication with Sampled Compression Ratio	Distributed, Parallel, and Cluster Computing (cs.DC)	Zhaoyang Du, Yijin Guan, Tianchan Guan, Dimin Niu, Nianxiong Tan, Xiaopeng Yu, Hongzhong Zheng, Jianyi Meng, Xiaolang Yan, Yuan Xie
2207.14200	CrAM: A Compression-Aware Minimizer	Machine Learning (cs.LG)	Alexandra Peste, Adrian Vladu, Dan Alistarh, Christoph H. Lampert
2207.14273	CuDi: Curve Distillation for Efficient and Controllable Exposure Adjustment	Computer Vision and Pattern Recognition (cs.CV)	Chongyi Li, Chunle Guo, Ruicheng Feng, Shangchen Zhou, Chen Change Loy
2207.14507	GPU-accelerated SIFT-aided source identification of stabilized videos	Computer Vision and Pattern Recognition (cs.CV)	Andrea Montibeller, Cecilia Pasquini, Giulia Boato, Stefano Dell'Anna, Fernando Pérez-González
2207.14545	A One-Shot Reparameterization Method for Reducing the Loss of Tile Pruning on DNNs	Computer Vision and Pattern Recognition (cs.CV)	Yanchen Li, Qingzhong Ai, Fumihiko Ino
2207.14676	Global-Local Self-Distillation for Visual Representation Learning	Computer Vision and Pattern Recognition (cs.CV)	Tim Lebailly, Tinne Tuytelaars
2207.14678	AlphaVC: High-Performance and Efficient Learned Video Compression	Computer Vision and Pattern Recognition (cs.CV)	Yibo Shi, Yunying Ge, Jing Wang, Jue Mao
2207.14686	Forensic License Plate Recognition with Compression-Informed Transformers	Computer Vision and Pattern Recognition (cs.CV)	Denise Moussa, Anatol Maier, Andreas Spruck, Jürgen Seiler, Christian Riess
2207.14696	BiFeat: Supercharge GNN Training via Graph Feature Quantization	Machine Learning (cs.LG)	Yuxin Ma, Ping Gong, Jun Yi, Zhewei Yao, Minjie Wang, Cheng Li, Yuxiong He, Feng Yan
2207.14757	ALADIN: Distilling Fine-grained Alignment Scores for Efficient Image-Text Matching and Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Nicola Messina, Matteo Stefanini, Marcella Cornia, Lorenzo Baraldi, Fabrizio Falchi, Giuseppe Amato, Rita Cucchiara
2208.00164	Distilled Low Rank Neural Radiance Field with Quantization for Light Field Compression	Computer Vision and Pattern Recognition (cs.CV)	Jinglei Shi, Christine Guillemot
2208.00338	Symmetry Regularization and Saturating Nonlinearity for Robust Quantization	Machine Learning (cs.LG)	Sein Park, Yeongsang Jang, Eunhyeok Park
2208.00351	Chinese grammatical error correction based on knowledge distillation	Computation and Language (cs.CL)	Peng Xia, Yuechi Zhou, Ziyan Zhang, Zecheng Tang, Juntao Li
2208.00449	SdAE: Self-distillated Masked Autoencoder	Computer Vision and Pattern Recognition (cs.CV)	Yabo Chen, Yuchen Liu, Dongsheng Jiang, Xiaopeng Zhang, Wenrui Dai, Hongkai Xiong, Qi Tian
2208.00777	$\textrm{D}^3\textrm{Former}$: Debiased Dual Distilled Transformer for Incremental Learning	Computer Vision and Pattern Recognition (cs.CV)	Abdelrahman Mohamed, Rushali Grandhe, KJ Joseph, Salman Khan, Fahad Khan
2208.00885	Many-to-One Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Internet of Things Systems	Signal Processing (eess.SP)	Saleh Baghersalimi, Alireza Amirshahi, Farnaz Forooghifar, Tomas Teijeiro, Amir Aminifar, David Atienza
2208.01302	Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction	Computer Vision and Pattern Recognition (cs.CV)	Xiaoning Sun, Qiongjie Cui, Huaijiang Sun, Bin Li, Weiqing Li, Jianfeng Lu
2208.01313	Unified Normalization for Accelerating and Stabilizing Transformers	Computer Vision and Pattern Recognition (cs.CV)	Qiming Yang, Kai Zhang, Chaoxiang Lan, Zhi Yang, Zheyang Li, Wenming Tan, Jun Xiao, Shiliang Pu
2208.01687	Neural Basis Functions for Accelerating Solutions to High Mach Euler Equations	Machine Learning (cs.LG)	David Witman, Alexander New, Hicham Alkendry, Honest Mrema
2208.01948	Decay2Distill: Leveraging spatial perturbation and regularization for self-supervised image denoising	Computer Vision and Pattern Recognition (cs.CV)	Manisha Das Chaity, Masud An Nur Islam Fahim
2208.02178	KD-SCFNet: Towards More Accurate and Efficient Salient Object Detection via Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Jin Zhang, Qiuwei Liang, Yanjiao Shi
2208.02459	Privacy-Preserving Action Recognition via Motion Difference Quantization	Computer Vision and Pattern Recognition (cs.CV)	Sudhakar Kumawat, Hajime Nagahara
2208.02519	IPDAE: Improved Patch-Based Deep Autoencoder for Lossy Point Cloud Geometry Compression	Computer Vision and Pattern Recognition (cs.CV)	Kang You, Pan Gao, Qing Li
2208.03006	Task-Balanced Distillation for Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Ruining Tang, Zhenyu Liu, Yangguang Li, Yiguo Song, Hui Liu, Qide Wang, Jing Shao, Guifang Duan, Jianrong Tan
2208.03075	PGX: A Multi-level GNN Explanation Framework Based on Separate Knowledge Distillation Processes	Machine Learning (cs.LG)	Tien-Cuong Bui, Wen-syan Li, Sang-Kyun Cha
2208.03763	Label Semantic Knowledge Distillation for Unbiased Scene Graph Generation	Computer Vision and Pattern Recognition (cs.CV)	Lin Li, Long Chen, Hanrong Shi, Wenxiao Wang, Jian Shao, Yi Yang, Jun Xiao
2208.04226	SKDCGN: Source-free Knowledge Distillation of Counterfactual Generative Networks using cGANs	Computer Vision and Pattern Recognition (cs.CV)	Sameer Ambekar, Matteo Tafuro, Ankit Ankit, Diego van der Mast, Mark Alence, Christos Athanasiadis
2208.04588	SBPF: Sensitiveness Based Pruning Framework For Convolutional Neural Network On Image Classification	Computer Vision and Pattern Recognition (cs.CV)	Yiheng Lu, Maoguo Gong, Wei Zhao, Kaiyuan Feng, Hao Li
2208.04952	Continual Prune-and-Select: Class-incremental learning with specialized subnetworks	Machine Learning (cs.LG)	Aleksandr Dekhovich, David M.J. Tax, Marcel H.F. Sluiter, Miguel A. Bessa
2208.05642	Self-Knowledge Distillation via Dropout	Computer Vision and Pattern Recognition (cs.CV)	Hyoje Lee, Yeachan Park, Hyun Seo, Myungjoo Kang
2208.05648	Embedding Compression with Hashing for Efficient Representation Learning in Large-Scale Graph	Machine Learning (cs.LG)	Chin-Chia Michael Yeh, Mengting Gu, Yan Zheng, Huiyuan Chen, Javid Ebrahimi, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang
2208.05669	PA-Seg: Learning from Point Annotations for 3D Medical Image Segmentation using Contextual Regularization and Cross Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Shuwei Zhai, Guotai Wang, Xiangde Luo, Qiang Yue, Kang Li, Shaoting Zhang
2208.05768	MixSKD: Self-Knowledge Distillation from Mixup for Image Recognition	Computer Vision and Pattern Recognition (cs.CV)	Chuanguang Yang, Zhulin An, Helong Zhou, Linhang Cai, Xiang Zhi, Jiwen Wu, Yongjun Xu, Qian Zhang
2208.05814	Seeing your sleep stage: cross-modal distillation from EEG to infrared video	Computer Vision and Pattern Recognition (cs.CV)	Jianan Han, Shaoxing Zhang, Aidong Men, Yang Liu, Ziming Yao, Yan Yan, Qingchao Chen
2208.05964	Forecasting the production of Distillate Fuel Oil Refinery and Propane Blender net production by using Time Series Algorithms	Machine Learning (cs.LG)	Akshansh Mishra, Rakesh Morisetty, Rajat Sarawagi
2208.05969	Safety and Performance, Why not Both? Bi-Objective Optimized Model Compression toward AI Software Deployment	Machine Learning (cs.LG)	Jie Zhu, Leye Wang, Xiao Han
2208.05970	WeightMom: Learning Sparse Networks using Iterative Momentum-based pruning	Machine Learning (cs.LG)	Elvis Johnson, Xiaochen Tang, Sriramacharyulu Samudrala
2208.06058	An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification	Machine Learning (cs.LG)	Runxue Bao, Bin Gu, Heng Huang
2208.06176	A Knowledge Distillation-Based Backdoor Attack in Federated Learning	Machine Learning (cs.LG)	Yifan Wang, Wei Fan, Keke Yang, Naji Alhusaini, Jing Li
2208.06183	Non-Autoregressive Sign Language Production via Knowledge Distillation	Machine Learning (cs.LG)	Eui Jun Hwang, Jung Ho Kim, Suk Min Cho, Jong C. Park
2208.06332	Accelerating Task-based Iterative Applications	Distributed, Parallel, and Cluster Computing (cs.DC)	David Álvarez, Vicenç Beltran
2208.06464	View Sub-sampling and Reconstruction for Efficient Light Field Compression	Computer Vision and Pattern Recognition (cs.CV)	Yang Chen, Martin Alain, Aljosa Smolic
2208.06660	Entropy Induced Pruning Framework for Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Yiheng Lu, Ziyu Guan, Yaming Yang, Maoguo Gong, Wei Zhao, Kaiyuan Feng
2208.06678	A new way of video compression via forward-referencing using deep learning	Computer Vision and Pattern Recognition (cs.CV)	S.M.A.K. Rajin, M. Murshed, M. Paul, S.W. Teng, J. Ma
2208.07023	Acceleration of Subspace Learning Machine via Particle Swarm Optimization and Parallel Processing	Machine Learning (cs.LG)	Hongyu Fu, Yijing Yang, Yuhuai Liu, Joseph Lin, Ethan Harrison, Vinod K. Mishra, C.-C. Jay Kuo
2208.07211	RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation	Machine Learning (cs.LG)	Yao Zhang, Yun Xiong, Yiheng Sun, Caihua Shan, Tian Lu, Hui Song, Yangyong Zhu
2208.08004	Field-wise Embedding Size Search via Structural Hard Auxiliary Mask Pruning for Click-Through Rate Prediction	Information Retrieval (cs.IR)	Tesi Xiao, Xia Xiao, Ming Chen, Youlong Chen
2208.08090	Progressive Cross-modal Knowledge Distillation for Human Action Recognition	Computer Vision and Pattern Recognition (cs.CV)	Jianyuan Ni, Anne H.H. Ngu, Yan Yan
2208.08566	Physical Computing for Materials Acceleration Platforms	Artificial Intelligence (cs.AI)	Erik Peterson, Alexander Lavin
2208.08677	Enhancing Targeted Attack Transferability via Diversified Weight Pruning	Computer Vision and Pattern Recognition (cs.CV)	Hung-Jui Wang, Yu-Yu Wu, Shang-Tse Chen
2208.08705	Adaptive Pulse Compression for Sidelobes Reduction in Stretch Processing based MIMO Radars	Signal Processing (eess.SP)	Hamza Malik, Jehanzeb Burki, Muhammad Zeeshan Mumtaz
2208.08741	Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification	Machine Learning (cs.LG)	Quanshi Zhang, Xu Cheng, Yilan Chen, Zhefan Rao
2208.08840	Mind the Gap in Distilling StyleGANs	Computer Vision and Pattern Recognition (cs.CV)	Guodong Xu, Yuenan Hou, Ziwei Liu, Chen Change Loy
2208.09139	DAFT: Distilling Adversarially Fine-tuned Models for Better OOD Generalization	Machine Learning (cs.LG)	Anshul Nasery, Sravanti Addepalli, Praneeth Netrapalli, Prateek Jain
2208.09225	FP8 Quantization: The Power of the Exponent	Machine Learning (cs.LG)	Andrey Kuzmin, Mart Van Baalen, Yuwei Ren, Markus Nagel, Jorn Peters, Tijmen Blankevoort
2208.09520	Accelerating Vision Transformer Training via a Patch Sampling Schedule	Computer Vision and Pattern Recognition (cs.CV)	Bradley McDanel, Chi Phuong Huynh
2208.09684	Combining Compressions for Multiplicative Size Scaling on Natural Language Tasks	Computation and Language (cs.CL)	Rajiv Movva, Jinhao Lei, Shayne Longpre, Ajay Gupta, Chris DuBois
2208.09828	I Know What You Do Not Know: Knowledge Graph Embedding via Co-distillation Learning	Computation and Language (cs.CL)	Yang Liu, Zequn Sun, Guangyao Li, Wei Hu
2208.10008	An Improved Ray Tracing Acceleration Algorithm Based on Bounding Volume Hierarchies	Signal Processing (eess.SP)	Chen Wang, Yinghua Wang, Yuxiao Li, Jialing Huang, Jie Huang, Cheng-Xiang Wang
2208.10139	Rethinking Knowledge Distillation via Cross-Entropy	Computer Vision and Pattern Recognition (cs.CV)	Zhendong Yang, Zhe Li, Yuan Gong, Tianke Zhang, Shanshan Lao, Chun Yuan, Yu Li
2208.10160	PANDA: Prompt Transfer Meets Knowledge Distillation for Efficient Model Adaptation	Computation and Language (cs.CL)	Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, Dacheng Tao
2208.10169	Multi-Granularity Distillation Scheme Towards Lightweight Semi-Supervised Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Jie Qin, Jie Wu, Ming Li, Xuefeng Xiao, Min Zheng, Xingang Wang
2208.10888	Joint Privacy Enhancement and Quantization in Federated Learning	Machine Learning (cs.LG)	Natalie Lang, Elad Sofer, Tomer Shaked, Nir Shlezinger
2208.11246	Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion	Machine Learning (cs.LG)	Gavin Zhang, Hong-Ming Chiu, Richard Y. Zhang
2208.11311	Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environments	Machine Learning (cs.LG)	Rui Song, Dai Liu, Dave Zhenyu Chen, Andreas Festag, Carsten Trinitis, Martin Schulz, Alois Knoll
2208.11499	Semi-supervised Semantic Segmentation with Mutual Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Jianlong Yuan, Jinchao Ge, Qi Qian, Zhibin Wang, Fan Wang, Yifan Liu
2208.11580	Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning	Machine Learning (cs.LG)	Elias Frantar, Dan Alistarh
2208.11596	A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing	Machine Learning (cs.LG)	Parual Datta, Nilesh Ahuja, V. Srinivasa Somayazulu, Omesh Tickoo
2208.11628	Debias the Black-box: A Fair Ranking Framework via Knowledge Distillation	Information Retrieval (cs.IR)	Zhitao Zhu, Shijing Si, Jianzong Wang, Yaodong Yang, Jing Xiao
2208.11669	Towards Sparsified Federated Neuroimaging Models via Weight Pruning	Machine Learning (cs.LG)	Dimitris Stripelis, Umang Gupta, Nikhil Dhinagar, Greg Ver Steeg, Paul Thompson, José Luis Ambite
2208.11673	Learned Lossless JPEG Transcoding via Joint Lossy and Residual Compression	Computer Vision and Pattern Recognition (cs.CV)	Xiaoshuai Fan, Xin Li, Zhibo Chen
2208.11945	Efficient Activation Quantization via Adaptive Rounding Border for Post-Training Quantization	Machine Learning (cs.LG)	Zhengyi Li, Cong Guo, Zhanda Zhu, Yangjie Zhou, Yuxian Qiu, Xiaotian Gao, Jingwen Leng, Minyi Guo
2208.12256	Masked Autoencoders Enable Efficient Knowledge Distillers	Computer Vision and Pattern Recognition (cs.CV)	Yutong Bai, Zeyu Wang, Junfei Xiao, Chen Wei, Huiyu Wang, Alan Yuille, Yuyin Zhou, Cihang Xie
2208.12262	MaskCLIP: Masked Self-Distillation Advances Contrastive Language-Image Pretraining	Computer Vision and Pattern Recognition (cs.CV)	Xiaoyi Dong, Yinglin Zheng, Jianmin Bao, Ting Zhang, Dongdong Chen, Hao Yang, Ming Zeng, Weiming Zhang, Lu Yuan, Dong Chen, Fang Wen, Nenghai Yu
2208.12448	CMD: Self-supervised 3D Action Representation Learning with Cross-modal Mutual Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yunyao Mao, Wengang Zhou, Zhenbo Lu, Jiajun Deng, Houqiang Li
2208.12464	Data-free Dense Depth Distillation	Computer Vision and Pattern Recognition (cs.CV)	Junjie Hu, Chenyou Fan, Mete Ozay, Hualie Jiang, Tin Lun Lam
2208.12573	Efficient LiDAR Point Cloud Geometry Compression Through Neighborhood Point Attention	Computer Vision and Pattern Recognition (cs.CV)	Ruixiang Xue, Jianqiang Wang, Zhan Ma
2208.12681	Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from A Conditional Causal Perspective	Computer Vision and Pattern Recognition (cs.CV)	Jiangmeng Li, Yanan Zhang, Wenwen Qiang, Lingyu Si, Chengbo Jiao, Xiaohui Hu, Changwen Zheng, Fuchun Sun
2208.12716	Multi-Scale Architectures Matter: On the Adversarial Robustness of Flow-based Lossless Compression	Computer Vision and Pattern Recognition (cs.CV)	Yi-chong Xia, Bin Chen, Yan Feng, Tian-shuo Ge
2208.12786	LUCID: Exposing Algorithmic Bias through Inverse Design	Machine Learning (cs.LG)	Carmen Mazijn, Carina Prunkl, Andres Algaba, Jan Danckaert, Vincent Ginis
2208.12816	Complexity-Driven CNN Compression for Resource-constrained Edge AI	Machine Learning (cs.LG)	Muhammad Zawish, Steven Davy, Lizy Abraham
2208.13092	Federated Sparse Training: Lottery Aware Model Compression for Resource Constrained Edge	Machine Learning (cs.LG)	Sara Babakniya, Souvik Kundu, Saurav Prakash, Yue Niu, Salman Avestimehr
2208.13298	Goal-Conditioned Q-Learning as Knowledge Distillation	Machine Learning (cs.LG)	Alexander Levine, Soheil Feizi
2208.13404	Progressive Self-Distillation for Ground-to-Aerial Perception Knowledge Transfer	Computer Vision and Pattern Recognition (cs.CV)	Junjie Hu, Chenyou Fan, Hua Feng, Yuan Gao, Tin Lun Lam
2208.13472	Supporting Medical Relation Extraction via Causality-Pruned Semantic Dependency Forest	Computation and Language (cs.CL)	Yifan Jin, Jiangmeng Li, Zheng Lian, Chengbo Jiao, Xiaohui Hu
2208.13605	Approach of variable clustering and compression for learning large Bayesian networks	Machine Learning (stat.ML)	Anna V. Bubnova
2208.13648	How to Teach: Learning Data-Free Knowledge Distillation from Curriculum	Computer Vision and Pattern Recognition (cs.CV)	Jingru Li, Sheng Zhou, Liangcheng Li, Xifeng Yan, Zhi Yu, Jiajun Bu
2208.14143	FAKD: Feature Augmented Knowledge Distillation for Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Jianlong Yuan, Qian Qi, Fei Du, Zhibin Wang, Fan Wang, Yifan Liu
2208.14286	ANT: Exploiting Adaptive Numerical Data Type for Low-bit Deep Neural Network Quantization	Machine Learning (cs.LG)	Cong Guo, Chen Zhang, Jingwen Leng, Zihan Liu, Fan Yang, Yunxin Liu, Minyi Guo, Yuhao Zhu
2208.14619	Accelerating differential evolution algorithm with Gaussian sampling based on estimating the convergence points	Neural and Evolutionary Computing (cs.NE)	Rui Zhong, Masaharu Munetomo
2208.14839	QuantNAS for super resolution: searching for efficient quantization-friendly architectures against quantization noise	Computer Vision and Pattern Recognition (cs.CV)	Egor Shvetsov, Dmitry Osin, Alexey Zaytsev, Ivan Koryakovskiy, Valentin Buchnev, Ilya Trofimov, Evgeny Burnaev
2208.14935	HyTGraph: GPU-Accelerated Graph Processing with Hybrid Transfer Management	Distributed, Parallel, and Cluster Computing (cs.DC)	Qiange Wang, Xin Ai, Yanfeng Zhang, Jing Chen, Ge Yu
2209.00519	A New Knowledge Distillation Network for Incremental Few-Shot Surface Defect Detection	Computer Vision and Pattern Recognition (cs.CV)	Chen Sun, Liang Gao, Xinyu Li, Yiping Gao
2209.00606	Sparse Attention Acceleration with Synergistic In-Memory Pruning and On-Chip Recomputation	Machine Learning (cs.LG)	Amir Yazdanbakhsh, Ashkan Moradifirouzabadi, Zheng Li, Mingu Kang
2209.00625	SwiftPruner: Reinforced Evolutionary Pruning for Efficient Ad Relevance	Information Retrieval (cs.IR)	Li Lyna Zhang, Youkow Homma, Yujing Wang, Min Wu, Mao Yang, Ruofei Zhang, Ting Cao, Wei Shen
2209.01115	Distilling Facial Knowledge With Teacher-Tasks: Semantic-Segmentation-Features For Pose-Invariant Face-Recognition	Computer Vision and Pattern Recognition (cs.CV)	Ali Hassani, Zaid El Shair, Rafi Ud Duala Refat, Hafiz Malik
2209.01311	A Novel Self-Knowledge Distillation Approach with Siamese Representation Learning for Action Recognition	Computer Vision and Pattern Recognition (cs.CV)	Duc-Quang Vu, Trang Phung, Jia-Ching Wang
2209.01868	Optimized Precoding for MU-MIMO With Fronthaul Quantization	Signal Processing (eess.SP)	Yasaman Khorsandmanesh, Emil Björnson, Joakim Jaldén
2209.02030	Distilling the Knowledge of BERT for CTC-based ASR	Computation and Language (cs.CL)	Hayato Futami, Hirofumi Inaguma, Masato Mimura, Shinsuke Sakai, Tatsuya Kawahara
2209.02201	What to Prune and What Not to Prune at Initialization	Neural and Evolutionary Computing (cs.NE)	Maham Haroon
2209.02432	ViTKD: Practical Guidelines for ViT feature knowledge distillation	Computer Vision and Pattern Recognition (cs.CV)	Zhendong Yang, Zhe Li, Ailing Zeng, Zexian Li, Chun Yuan, Yu Li
2209.02869	Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps	Computer Vision and Pattern Recognition (cs.CV)	Alireza Ganjdanesh, Shangqian Gao, Heng Huang
2209.03357	Distilling Deep RL Models Into Interpretable Neuro-Fuzzy Systems	Machine Learning (cs.LG)	Arne Gevaert, Jonathan Peck, Yvan Saeys
2209.03494	Neural Feature Fusion Fields: 3D Distillation of Self-Supervised 2D Image Representations	Computer Vision and Pattern Recognition (cs.CV)	Vadim Tschernezki, Iro Laina, Diane Larlus, Andrea Vedaldi
2209.03534	CWP: Instance complexity weighted channel-wise soft masks for network pruning	Machine Learning (cs.LG)	Jiapeng Wang, Ming Ma, Zhenhua Yu
2209.03603	nVFNet-RDC: Replay and Non-Local Distillation Collaboration for Continual Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Jinxiang Lai, Wenlong Liu, Jun Liu
2209.03997	Online Low Rank Matrix Completion	Machine Learning (cs.LG)	Prateek Jain, Soumyabrata Pal
2209.04130	In-situ animal behavior classification using knowledge distillation and fixed-point quantization	Machine Learning (cs.LG)	Reza Arablouei, Liang Wang, Caitlin Phillips, Lachlan Currie, Jordan Yates, Greg Bishop-Hurley
2209.04996	Switchable Online Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Biao Qian, Yang Wang, Hongzhi Yin, Richang Hong, Meng Wang
2209.05148	Personalized Federated Learning with Communication Compression	Machine Learning (cs.LG)	El Houcine Bergou, Konstantin Burlachenko, Aritra Dutta, Peter Richtárik
2209.05234	Low rank prior and l0 norm to remove impulse noise in images	Computer Vision and Pattern Recognition (cs.CV)	Haijuan Hu
2209.05683	One-shot Network Pruning at Initialization with Discriminative Image Patches	Computer Vision and Pattern Recognition (cs.CV)	Yinan Yang, Yu Wang, Ying Ji, Heng Qi, Jien Kato
2209.05687	PSAQ-ViT V2: Towards Accurate and General Data-Free Quantization for Vision Transformers	Computer Vision and Pattern Recognition (cs.CV)	Zhikai Li, Mengjuan Chen, Junrui Xiao, Qingyi Gu
2209.05869	Multi-stage Distillation Framework for Cross-Lingual Semantic Similarity Matching	Computation and Language (cs.CL)	Kunbo Ding, Weijie Liu, Yuejian Fang, Zhe Zhao, Qi Ju, Xuefeng Yang
2209.05924	SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud Representation	Computer Vision and Pattern Recognition (cs.CV)	Zhuo Su, Max Welling, Matti Pietikäinen, Li Liu
2209.06107	Online Continual Learning via the Meta-learning Update with Multi-scale Knowledge Distillation and Data Augmentation	Machine Learning (cs.LG)	Ya-nan Han, Jian-wei Liu
2209.06359	Federated Pruning: Improving Neural Network Efficiency with Federated Learning	Machine Learning (cs.LG)	Rongmei Lin, Yonghui Xiao, Tien-Ju Yang, Ding Zhao, Li Xiong, Giovanni Motta, Françoise Beaufays
2209.06383	Analysis of Quantization on MLP-based Vision Models	Computer Vision and Pattern Recognition (cs.CV)	Lingran Zhao, Zhen Dong, Kurt Keutzer
2209.07076	Responsible AI Implementation: A Human-centered Framework for Accelerating the Innovation Process	Artificial Intelligence (cs.AI)	Dian Tjondronegoro, Elizabeth Yuwono, Brent Richards, Damian Green, Siiri Hatakka
2209.07080	Layerwise Bregman Representation Learning with Applications to Knowledge Distillation	Machine Learning (cs.LG)	Ehsan Amid, Rohan Anil, Christopher Fifty, Manfred K. Warmuth
2209.07088	Self-distilled Feature Aggregation for Self-supervised Monocular Depth Estimation	Computer Vision and Pattern Recognition (cs.CV)	Zhengming Zhou, Qiulei Dong
2209.07258	Graph-to-Text Generation with Dynamic Structure Pruning	Computation and Language (cs.CL)	Liang Li, Ruiying Geng, Bowen Li, Can Ma, Yinliang Yue, Binhua Li, Yongbin Li
2209.07606	CES-KD: Curriculum-based Expert Selection for Guided Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Ibtihel Amara, Maryam Ziaeefard, Brett H. Meyer, Warren Gross, James J. Clark
2209.07617	Training Recipe for N:M Structured Sparsity with Decaying Pruning Mask	Machine Learning (cs.LG)	Sheng-Chun Kao, Amir Yazdanbakhsh, Suvinay Subramanian, Shivani Agrawal, Utku Evci, Tushar Krishna
2209.07809	M$^2$DQN: A Robust Method for Accelerating Deep Q-learning Network	Machine Learning (cs.LG)	Zhe Zhang, Yukun Zou, Junjie Lai, Qing Xu
2209.08194	PPT: token-Pruned Pose Transformer for monocular and multi-view human pose estimation	Computer Vision and Pattern Recognition (cs.CV)	Haoyu Ma, Zhe Wang, Yifei Chen, Deying Kong, Liangjian Chen, Xingwei Liu, Xiangyi Yan, Hao Tang, Xiaohui Xie
2209.08276	CARNet:Compression Artifact Reduction for Point Cloud Attribute	Computer Vision and Pattern Recognition (cs.CV)	Dandan Ding, Junzhe Zhang, Jianqiang Wang, Zhan Ma
2209.08452	MetaDIP: Accelerating Deep Image Prior with Meta Learning	Computer Vision and Pattern Recognition (cs.CV)	Kevin Zhang, Mingyang Xie, Maharshi Gor, Yi-Ting Chen, Yvonne Zhou, Christopher A. Metzler
2209.08554	Pruning Neural Networks via Coresets and Convex Geometry: Towards No Assumptions	Machine Learning (cs.LG)	Murad Tukan, Loay Mualem, Alaa Maalouf
2209.08617	PIM-QAT: Neural Network Quantization for Processing-In-Memory (PIM) Systems	Machine Learning (cs.LG)	Qing Jin, Zhiyu Chen, Jian Ren, Yanyu Li, Yanzhi Wang, Kaiyuan Yang
2209.08754	Toward Understanding Privileged Features Distillation in Learning-to-Rank	Machine Learning (cs.LG)	Shuo Yang, Sujay Sanghavi, Holakou Rahmanian, Jan Bakus, S.V.N. Vishwanathan
2209.09092	TASKED: Transformer-based Adversarial learning for human activity recognition using wearable sensors via Self-KnowledgE Distillation	Computer Vision and Pattern Recognition (cs.CV)	Sungho Suh, Vitor Fortes Rey, Paul Lukowicz
2209.09621	Scaling and compressing melodies using geometric similarity measures	Information Retrieval (cs.IR)	Luis Evaristo Caraballo, José Miguel Díaz-Báñez, Fabio Rodríguez, Vanesa Sánchez-Canales, Inmaculada Ventura
2209.09731	Early Application Experiences on a Modern GPU-Accelerated Arm-based HPC Platform	Distributed, Parallel, and Cluster Computing (cs.DC)	Wael Elwasif, Sergei Bastrakov, Spencer H. Bryngelson, Michael Bussmann, Sunita Chandrasekaran, Florina Ciorba, M. A. Clark, Alexander Debus, William Godoy, Nick Hagerty, Jeff Hammond, David Hardy, J. Austin Harris, Oscar Hernandez, Balint Joo, Sebastian Keller, Paul Kent, Henry Le Berre, Damien Lebrun-Grandie, Elijah MacCarthy, Verónica G. Melesse Vergara, Bronson Messer, Ross Miller, Sarp Oral, Jean-Guillaume Piccinali, Anand Radhakrishnan, Osman Simsek, Filippo Spiga, Klaus Steiniger, Jan Stephan, John E. Stone, Christian Trott, René Widera, Jeffrey Young
2209.09841	Rethinking Data Augmentation in Knowledge Distillation for Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Jiawei Liang, Siyuan Liang, Aishan Liu, Mingli Zhu, Danni Yuan, Chenye Xu, Xiaochun Cao
2209.10359	Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Kien Do, Hung Le, Dung Nguyen, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh
2209.10890	EPIC TTS Models: Empirical Pruning Investigations Characterizing Text-To-Speech Models	Audio and Speech Processing (eess.AS)	Perry Lam, Huayun Zhang, Nancy F. Chen, Berrak Sisman
2209.10907	DRKF: Distilled Rotated Kernel Fusion for Efficiently Boosting Rotation Invariance in Image Matching	Computer Vision and Pattern Recognition (cs.CV)	Chao Li, Jiancheng Cai, Ranran Huang, Xinmin Liu
2209.11228	NamedMask: Distilling Segmenters from Complementary Foundation Models	Computer Vision and Pattern Recognition (cs.CV)	Gyungin Shin, Weidi Xie, Samuel Albanie
2209.11785	Tiered Pruning for Efficient Differentialble Inference-Aware Neural Architecture Search	Machine Learning (cs.LG)	Sławomir Kierat, Mateusz Sieniawski, Denys Fridman, Chen-Han Yu, Szymon Migacz, Paweł Morkisz, Alex-Fit Florea
2209.11795	Descriptor Distillation: a Teacher-Student-Regularized Framework for Learning Local Descriptors	Computer Vision and Pattern Recognition (cs.CV)	Yuzhen Liu, Qiulei Dong
2209.12139	Lightweight Image Codec via Multi-Grid Multi-Block-Size Vector Quantization (MGBVQ)	Computer Vision and Pattern Recognition (cs.CV)	Yifan Wang, Zhanxuan Mei, Ioannis Katsavounidis, C.-C. Jay Kuo
2209.12310	Accelerating the Convex Hull Computation with a Parallel GPU Algorithm	Distributed, Parallel, and Cluster Computing (cs.DC)	Alan Keith, Héctor Ferrada, Cristóbal A. Navarro
2209.12420	Knowledge Distillation to Ensemble Global and Interpretable Prototype-Based Mammogram Classification Models	Computer Vision and Pattern Recognition (cs.CV)	Chong Wang, Yuanhong Chen, Yuyuan Liu, Yu Tian, Fengbei Liu, Davis J. McCarthy, Michael Elliott, Helen Frazer, Gustavo Carneiro
2209.12744	Baking in the Feature: Accelerating Volumetric Segmentation by Rendering Feature Maps	Computer Vision and Pattern Recognition (cs.CV)	Kenneth Blomqvist, Lionel Ott, Jen Jen Chung, Roland Siegwart
2209.12816	Fast-FNet: Accelerating Transformer Encoder Models via Efficient Fourier Layers	Computation and Language (cs.CL)	Nurullah Sevim, Ege Ozan Özyedek, Furkan Şahinuç, Aykut Koç
2209.13077	Accelerating the Genetic Algorithm for Large-scale Traveling Salesman Problems by Cooperative Coevolutionary Pointer Network with Reinforcement Learning	Neural and Evolutionary Computing (cs.NE)	Rui Zhong, Enzhi Zhang, Masaharu Munetomo
2209.13280	Improving Pulse-Compression Weather Radar via the Joint Design of Subpulses and Extended Mismatch Filter	Signal Processing (eess.SP)	Linlong Wu, Mohammad Alaee-Kerahroodi, M. R. Bhavani Shankar
2209.13335	PROD: Progressive Distillation for Dense Retrieval	Information Retrieval (cs.IR)	Zhenghao Lin, Yeyun Gong, Xiao Liu, Hang Zhang, Chen Lin, Anlei Dong, Jian Jiao, Jingwen Lu, Daxin Jiang, Rangan Majumder, Nan Duan
2209.13434	Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees)	Machine Learning (stat.ML)	Paul Novello, Gaël Poëtte, David Lugato, Simon Peluchon, Pietro Marco Congedo
2209.13569	Exploring Low Rank Training of Deep Neural Networks	Machine Learning (cs.LG)	Siddhartha Rao Kamalakara, Acyr Locatelli, Bharat Venkitesh, Jimmy Ba, Yarin Gal, Aidan N. Gomez
2209.13590	Sauron U-Net: Simple automated redundancy elimination in medical image segmentation via filter pruning	Computer Vision and Pattern Recognition (cs.CV)	Juan Miguel Valverde, Artem Shatillo, Jussi Tohka
2209.13762	Consensus Knowledge Graph Learning via Multi-view Sparse Low Rank Block Model	Machine Learning (stat.ML)	Tianxi Cai, Dong Xia, Luwan Zhang, Doudou Zhou
2209.13802	Adaptive Sparse ViT: Towards Learnable Adaptive Token Pruning by Fully Exploiting Self-Attention	Computer Vision and Pattern Recognition (cs.CV)	Xiangcheng Liu, Tianyi Wu, Guodong Guo
2209.14150	Speech Enhancement Using Self-Supervised Pre-Trained Model and Vector Quantization	Audio and Speech Processing (eess.AS)	Xiao-Ying Zhao, Qiu-Shi Zhu, Jie Zhang
2209.14201	Spatial Pruned Sparse Convolution for Efficient 3D Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Jianhui Liu, Yukang Chen, Xiaoqing Ye, Zhuotao Tian, Xiao Tan, Xiaojuan Qi
2209.14498	Teaching Where to Look: Attention Similarity Knowledge Distillation for Low Resolution Face Recognition	Computer Vision and Pattern Recognition (cs.CV)	Sungho Shin, Joosoon Lee, Junseok Lee, Yeonguk Yu, Kyoobin Lee
2209.14520	Label driven Knowledge Distillation for Federated Learning with non-IID Data	Machine Learning (cs.LG)	Minh-Duong Nguyen, Quoc-Viet Pham, Dinh Thai Hoang, Long Tran-Thanh, Diep N. Nguyen, Won-Joo Hwang
2209.14593	Denoising MCMC for Accelerating Diffusion-Based Generative Models	Machine Learning (cs.LG)	Beomsu Kim, Jong Chul Ye
2209.14609	Dataset Distillation using Parameter Pruning	Computer Vision and Pattern Recognition (cs.CV)	Guang Li, Ren Togo, Takahiro Ogawa, Miki Haseyama
2209.14624	Is Complexity Required for Neural Network Pruning? A Case Study on Global Magnitude Pruning	Machine Learning (cs.LG)	Manas Gupta, Efe Camci, Vishandi Rudy Keneta, Abhishek Vaidyanathan, Ritwik Kanodia, Chuan-Sheng Foo, Wu Min, Lin Jie
2209.14642	A Coarse-to-fine Cascaded Evidence-Distillation Neural Network for Explainable Fake News Detection	Computation and Language (cs.CL)	Zhiwei Yang, Jing Ma, Hechang Chen, Hongzhan Lin, Ziyang Luo, Yi Chang
2209.14827	On the Convergence of AdaGrad on $\R^{d}$: Beyond Convexity, Non-Asymptotic Rate and Acceleration	Machine Learning (cs.LG)	Zijian Liu, Ta Duy Nguyen, Alina Ene, Huy L. Nguyen
2209.15165	Distilling Style from Image Pairs for Global Forward and Inverse Tone Mapping	Computer Vision and Pattern Recognition (cs.CV)	Aamir Mustafa, Param Hanji, Rafal K. Mantiuk
2209.15189	Learning by Distilling Context	Computation and Language (cs.CL)	Charlie Snell, Dan Klein, Ruiqi Zhong
2209.15203	Downlink Compression Improves TopK Sparsification	Machine Learning (cs.LG)	William Zou, Hans De Sterck, Jun Liu
2209.15249	Experts in the Loop: Conditional Variable Selection for Accelerating Post-Silicon Analysis Based on Deep Learning	Machine Learning (cs.LG)	Yiwen Liao, Raphaël Latty, Bin Yang
2209.15317	Convolutional Neural Networks Quantization with Attention	Artificial Intelligence (cs.AI)	Binyi Wu, Bernd Waschneck, Christian Georg Mayr
2209.15347	Goal-Oriented Quantization: Analysis, Design, and Application to Resource Allocation	Signal Processing (eess.SP)	Hang Zou, Chao Zhang, Samson Lasaulce, Lucas Saludjian, Vincent Poor
2209.15496	Using Knowledge Distillation to improve interpretable models in a retail banking context	Machine Learning (cs.LG)	Maxime Biehler, Mohamed Guermazi, Célim Starck
2209.15505	Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data	Machine Learning (cs.LG)	Yuki Takezawa, Han Bao, Kenta Niwa, Ryoma Sato, Makoto Yamada
2209.15555	Towards a Unified View of Affinity-Based Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Vladimir Li, Atsuto Maki
2209.15560	Designing and Training of Lightweight Neural Networks on Edge Devices using Early Halting in Knowledge Distillation	Machine Learning (cs.LG)	Rahul Mishra, Hari Prabhat Gupta
2210.00066	Improving Policy Learning via Language Dynamics Distillation	Machine Learning (cs.LG)	Victor Zhong, Jesse Mu, Luke Zettlemoyer, Edward Grefenstette, Tim Rocktäschel
2210.00102	MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization	Machine Learning (cs.LG)	Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah
2210.00181	EAPruning: Evolutionary Pruning for Vision Transformers and CNNs	Computer Vision and Pattern Recognition (cs.CV)	Qingyuan Li, Bo Zhang, Xiangxiang Chu
2210.00944	Attention Distillation: self-supervised vision transformer students need more guidance	Computer Vision and Pattern Recognition (cs.CV)	Kai Wang, Fei Yang, Joost van de Weijer
2210.01213	Robust Active Distillation	Machine Learning (cs.LG)	Cenk Baykal, Khoa Trinh, Fotis Iliopoulos, Gaurav Menghani, Erik Vee
2210.01351	Less is More: Task-aware Layer-wise Distillation for Language Model Compression	Computation and Language (cs.CL)	Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao
2210.01600	Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification	Computer Vision and Pattern Recognition (cs.CV)	Kai Wang, Chenshen Wu, Andy Bagdanov, Xialei Liu, Shiqi Yang, Shangling Jui, Joost van de Weijer
2210.01701	Knowledge Distillation based Contextual Relevance Matching for E-commerce Product Search	Information Retrieval (cs.IR)	Ziyang Liu, Chaokun Wang, Hao Feng, Lingfei Wu, Liqun Yang
2210.01792	Sampling Streaming Data with Parallel Vector Quantization -- PVQ	Machine Learning (cs.LG)	Mujahid Sultan
2210.02019	Atari-5: Distilling the Arcade Learning Environment down to Five Games	Artificial Intelligence (cs.AI)	Matthew Aitchison, Penny Sweetser, Marcus Hutter
2210.02097	Teaching Yourself: Graph Self-Distillation on Neighborhood for Node Classification	Machine Learning (cs.LG)	Lirong Wu, Jun Xia, Haitao Lin, Zhangyang Gao, Zicheng Liu, Guojiang Zhao, Stan Z. Li
2210.02099	Automated Graph Self-supervised Learning via Multi-teacher Knowledge Distillation	Machine Learning (cs.LG)	Lirong Wu, Yufei Huang, Haitao Lin, Zicheng Liu, Tianyu Fan, Stan Z. Li
2210.02190	Domain Discrepancy Aware Distillation for Model Aggregation in Federated Learning	Machine Learning (cs.LG)	Shangchao Su, Bin Li, Xiangyang Xue
2210.02224	Neural Distillation as a State Representation Bottleneck in Reinforcement Learning	Machine Learning (cs.LG)	Valentin Guillet, Dennis G. Wilson, Carlos Aguilar-Melchor, Emmanuel Rachelson
2210.02227	Comprint: Image Forgery Detection and Localization using Compression Fingerprints	Computer Vision and Pattern Recognition (cs.CV)	Hannes Mareen, Dante Vanden Bussche, Fabrizio Guillaro, Davide Cozzolino, Glenn Van Wallendael, Peter Lambert, Luisa Verdoliva
2210.02768	Distilling Task-specific Logical Rules from Large Pre-trained Models	Computation and Language (cs.CL)	Tao Chen, Luxin Liu, Xuepeng Jia, Baoliang Cui, Haihong Tang, Siliang Tang
2210.02808	Effective Self-supervised Pre-training on Low-compute networks without Distillation	Computer Vision and Pattern Recognition (cs.CV)	Fuwen Tan, Fatemeh Saleh, Brais Martinez
2210.02871	Self-Distillation for Further Pre-training of Transformers	Computer Vision and Pattern Recognition (cs.CV)	Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi
2210.03142	On Distillation of Guided Diffusion Models	Computer Vision and Pattern Recognition (cs.CV)	Chenlin Meng, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans
2210.03162	Prompt Compression and Contrastive Conditioning for Controllability and Toxicity Reduction in Language Models	Computation and Language (cs.CL)	David Wingate, Mohammad Shoeybi, Taylor Sorensen
2210.03230	NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies	Machine Learning (cs.LG)	Arjun Krishnakumar, Colin White, Arber Zela, Renbo Tu, Mahmoud Safari, Frank Hutter
2210.03312	Distillation-Resistant Watermarking for Model Protection in NLP	Computation and Language (cs.CL)	Xuandong Zhao, Lei Li, Yu-Xiang Wang
2210.03477	IDa-Det: An Information Discrepancy-aware Distillation for 1-bit Detectors	Computer Vision and Pattern Recognition (cs.CV)	Sheng Xu, Yanjing Li, Bohan Zeng, Teli ma, Baochang Zhang, Xianbin Cao, Peng Gao, Jinhu Lv
2210.03505	Private and Efficient Meta-Learning with Low Rank and Sparse Decomposition	Machine Learning (cs.LG)	Soumyabrata Pal, Prateek Varshney, Prateek Jain, Abhradeep Guha Thakurta, Gagan Madan, Gaurav Aggarwal, Pradeep Shenoy, Gaurav Srivastava
2210.03625	C2KD: Cross-Lingual Cross-Modal Knowledge Distillation for Multilingual Text-Video Retrieval	Computation and Language (cs.CL)	Andrew Rouditchenko, Yung-Sung Chuang, Nina Shvetsova, Samuel Thomas, Rogerio Feris, Brian Kingsbury, Leonid Karlinsky, David Harwath, Hilde Kuehne, James Glass
2210.03664	Bi-directional Weakly Supervised Knowledge Distillation for Whole Slide Image Classification	Computer Vision and Pattern Recognition (cs.CV)	Linhao Qu, Xiaoyuan Luo, Manning Wang, Zhijian Song
2210.03692	Compressing Video Calls using Synthetic Talking Heads	Computer Vision and Pattern Recognition (cs.CV)	Madhav Agarwal, Anchit Gupta, Rudrabha Mukhopadhyay, Vinay P. Namboodiri, C V Jawahar
2210.03858	AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models	Machine Learning (cs.LG)	Se Jung Kwon, Jeonghoon Kim, Jeongin Bae, Kang Min Yoo, Jin-Hwa Kim, Baeseong Park, Byeongwook Kim, Jung-Woo Ha, Nako Sung, Dongsoo Lee
2210.03885	Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts	Machine Learning (cs.LG)	Tao Zhong, Zhixiang Chi, Li Gu, Yang Wang, Yuanhao Yu, Jin Tang
2210.03888	Accelerated and Deep Expectation Maximization for One-Bit MIMO-OFDM Detection	Signal Processing (eess.SP)	Mingjie Shao, Wing-Kin Ma, Junbin Liu, Zihao Huang
2210.03980	Distilling Causal Effect from Miscellaneous Other-Class for Continual Named Entity Recognition	Computation and Language (cs.CL)	Junhao Zheng, Zhanxian Liang, Haibin Chen, Qianli Ma
2210.04092	Advancing Model Pruning via Bi-level Optimization	Machine Learning (cs.LG)	Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu
2210.04311	Pruning Adversarially Robust Neural Networks without Adversarial Examples	Machine Learning (cs.LG)	Tong Jian, Zifeng Wang, Yanzhi Wang, Jennifer Dy, Stratis Ioannidis
2210.04398	Scaling Up Probabilistic Circuits by Latent Variable Distillation	Machine Learning (cs.LG)	Anji Liu, Honghua Zhang, Guy Van den Broeck
2210.04468	Distill the Image to Nowhere: Inversion Knowledge Distillation for Multimodal Machine Translation	Computation and Language (cs.CL)	Ru Peng, Yawen Zeng, Junbo Zhao
2210.04623	DeltaFS: Pursuing Zero Update Overhead via Metadata-Enabled Delta Compression for Log-structured File System on Mobile Devices	Distributed, Parallel, and Cluster Computing (cs.DC)	Chao Wu, Cheng Ji, Geng Yuan, Riwei Pan, Weichao Guo, Chao Yu, Zongwei Zhu, Yanzhi Wang
2210.04834	Knowledge Distillation Transfer Sets and their Impact on Downstream NLU Tasks	Computation and Language (cs.CL)	Charith Peris, Lizhen Tan, Thomas Gueudre, Turan Gojayev, Pan Wei, Gokmen Oz
2210.04847	NerfAcc: A General NeRF Acceleration Toolbox	Computer Vision and Pattern Recognition (cs.CV)	Ruilong Li, Matthew Tancik, Angjoo Kanazawa
2210.05033	Multilingual Representation Distillation with Contrastive Learning	Computation and Language (cs.CL)	Weiting Tan, Kevin Heffernan, Holger Schwenk, Philipp Koehn
2210.05111	Deep learning model compression using network sensitivity and gradients	Machine Learning (cs.LG)	Madhumitha Sakthi, Niranjan Yadla, Raj Pawate
2210.05247	Efficient debiasing with contrastive weight pruning	Machine Learning (cs.LG)	Geon Yeong Park, Sangmin Lee, Sang Wan Lee, Jong Chul Ye
2210.05248	Self-supervised debiasing using low rank regularization	Machine Learning (cs.LG)	Geon Yeong Park, Chanyong Jung, Jong Chul Ye, Sang Wan Lee
2210.05287	Revisiting and Advancing Chinese Natural Language Understanding with Accelerated Heterogeneous Knowledge Pre-training	Computation and Language (cs.CL)	Taolin Zhang, Junwei Dong, Jianing Wang, Chengyu Wang, Ang Wang, Yinghui Liu, Jun Huang, Yong Li, Xiaofeng He
2210.05355	Multi-User Reinforcement Learning with Low Rank Rewards	Machine Learning (cs.LG)	Naman Agarwal, Prateek Jain, Suhas Kowshik, Dheeraj Nagaraj, Praneeth Netrapalli
2210.05455	Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes	Machine Learning (cs.LG)	J. Hyam Rubinstein, Benjamin I. P. Rubinstein
2210.05709	Shapley Head Pruning: Identifying and Removing Interference in Multilingual Transformers	Computation and Language (cs.CL)	William Held, Diyi Yang
2210.05793	Comparison of Soft and Hard Target RNN-T Distillation for Large-scale ASR	Machine Learning (cs.LG)	Dongseong Hwang, Khe Chai Sim, Yu Zhang, Trevor Strohman
2210.05801	Linkless Link Prediction via Relational Distillation	Machine Learning (cs.LG)	Zhichun Guo, William Shiao, Shichang Zhang, Yozen Liu, Nitesh Chawla, Neil Shah, Tong Zhao
2210.05832	SaiT: Sparse Vision Transformers through Adaptive Token Pruning	Computer Vision and Pattern Recognition (cs.CV)	Ling Li, David Thorsley, Joseph Hassoun
2210.05920	Boosting Graph Neural Networks via Adaptive Knowledge Distillation	Machine Learning (cs.LG)	Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh Chawla
2210.05941	Decomposed Knowledge Distillation for Class-Incremental Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Donghyeon Baek, Youngmin Oh, Sanghoon Lee, Junghyup Lee, Bumsub Ham
2210.05991	Distilling Knowledge from Language Models for Video-based Action Anticipation	Computer Vision and Pattern Recognition (cs.CV)	Sayontan Ghosh, Tanvi Aggarwal, Minh Hoai, Niranjan Balasubramanian
2210.06210	Pruning Pre-trained Language Models Without Fine-Tuning	Computation and Language (cs.CL)	Ting Jiang, Deqing Wang, Fuzhen Zhuang
2210.06384	GMP*: Well-Tuned Global Magnitude Pruning Can Outperform Most BERT-Pruning Methods	Computation and Language (cs.CL)	Eldar Kurtic, Dan Alistarh
2210.06425	MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers	Computation and Language (cs.CL)	Mohammadmahdi Nouriborji, Omid Rohanian, Samaneh Kouchaki, David A. Clifton
2210.06458	Efficient Knowledge Distillation from Model Checkpoints	Machine Learning (cs.LG)	Chaofei Wang, Qisen Yang, Rui Huang, Shiji Song, Gao Huang
2210.06596	Reducing The Mismatch Between Marginal and Learned Distributions in Neural Video Compression	Computer Vision and Pattern Recognition (cs.CV)	Muhammet Balcilar, Bharath Bhushan Damodaran, Pierre Hellier
2210.06659	Structural Pruning via Latency-Saliency Knapsack	Computer Vision and Pattern Recognition (cs.CV)	Maying Shen, Hongxu Yin, Pavlo Molchanov, Lei Mao, Jianna Liu, Jose M. Alvarez
2210.06711	Weighted Distillation with Unlabeled Examples	Machine Learning (cs.LG)	Fotis Iliopoulos, Vasilis Kontonis, Cenk Baykal, Gaurav Menghani, Khoa Trinh, Erik Vee
2210.06814	Accelerating the Evolutionary Algorithms by Gaussian Process Regression with $ε$-greedy acquisition function	Neural and Evolutionary Computing (cs.NE)	Rui Zhong, Enzhi Zhang, Masaharu Munetomo
2210.06888	AccelAT: A Framework for Accelerating the Adversarial Training of Deep Neural Networks through Accuracy Gradient	Machine Learning (cs.LG)	Farzad Nikfam, Alberto Marchisio, Maurizio Martina, Muhammad Shafique
2210.07171	SQuAT: Sharpness- and Quantization-Aware Training for BERT	Machine Learning (cs.LG)	Zheng Wang, Juncheng B Li, Shuhui Qu, Florian Metze, Emma Strubell
2210.07189	On Compressing Sequences for Self-Supervised Speech Models	Computation and Language (cs.CL)	Yen Meng, Hsuan-Jui Chen, Jiatong Shi, Shinji Watanabe, Paola Garcia, Hung-yi Lee, Hao Tang
2210.07451	Neural Network Compression by Joint Sparsity Promotion and Redundancy Reduction	Computer Vision and Pattern Recognition (cs.CV)	Tariq M. Khan, Syed S. Naqvi, Antonio Robles-Kelly, Erik Meijering
2210.07686	Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation	Machine Learning (cs.LG)	Jieyi Bi, Yining Ma, Jiahai Wang, Zhiguang Cao, Jinbiao Chen, Yuan Sun, Yeow Meng Chee
2210.07760	Lightweight Alpha Matting Network Using Distillation-Based Channel Pruning	Computer Vision and Pattern Recognition (cs.CV)	Donggeun Yoon, Jinsun Park, Donghyeon Cho
2210.07795	EfficientVLM: Fast and Accurate Vision-Language Models via Knowledge Distillation and Modal-adaptive Pruning	Computation and Language (cs.CL)	Tiannan Wang, Wangchunshu Zhou, Yan Zeng, Xinsong Zhang
2210.07906	Post-Training Quantization for Energy Efficient Realization of Deep Neural Networks	Machine Learning (cs.LG)	Cecilia Latotzke, Batuhan Balim, Tobias Gemmeke
2210.08086	Knowledge Distillation approach towards Melanoma Detection	Computer Vision and Pattern Recognition (cs.CV)	Md. Shakib Khan, Kazi Nabiul Alam, Abdur Rab Dhruba, Hasib Zunair, Nabeel Mohammed
2210.08226	Self-Distillation for Unsupervised 3D Domain Adaptation	Computer Vision and Pattern Recognition (cs.CV)	Adriano Cardace, Riccardo Spezialetti, Pierluigi Zama Ramirez, Samuele Salti, Luigi Di Stefano
2210.08262	Motion estimation and filtered prediction for dynamic point cloud attribute compression	Computer Vision and Pattern Recognition (cs.CV)	Haoran Hong, Eduardo Pavez, Antonio Ortega, Ryosuke Watanabe, Keisuke Nonaka
2210.08388	RoS-KD: A Robust Stochastic Knowledge Distillation Approach for Noisy Medical Imaging	Computer Vision and Pattern Recognition (cs.CV)	Ajay Jaiswal, Kumar Ashutosh, Justin F Rousseau, Yifan Peng, Zhangyang Wang, Ying Ding
2210.08464	Federated Learning with Privacy-Preserving Ensemble Attention Distillation	Machine Learning (cs.LG)	Xuan Gong, Liangchen Song, Rishi Vedula, Abhishek Sharma, Meng Zheng, Benjamin Planche, Arun Innanje, Terrence Chen, Junsong Yuan, David Doermann, Ziyan Wu
2210.08485	HQNAS: Auto CNN deployment framework for joint quantization and architecture search	Machine Learning (cs.LG)	Hongjiang Chen, Yang Wang, Leibo Liu, Shaojun Wei, Shouyi Yin
2210.08650	Accelerating Transfer Learning with Near-Data Computation on Cloud Object Stores	Machine Learning (cs.LG)	Arsany Guirguis, Diana Petrescu, Florin Dinu, Do Le Quoc, Javier Picorel, Rachid Guerraoui
2210.08701	ODG-Q: Robust Quantization via Online Domain Generalization	Machine Learning (cs.LG)	Chaofan Tao, Ngai Wong
2210.08803	Merlin HugeCTR: GPU-accelerated Recommender System Training and Inference	Distributed, Parallel, and Cluster Computing (cs.DC)	Joey Wang, Yingcan Wei, Minseok Lee, Matthias Langer, Fan Yu, Jie Liu, Alex Liu, Daniel Abel, Gems Guo, Jianbing Dong, Jerry Shi, Kunlun Li
2210.08872	PTDE: Personalized Training with Distillated Execution for Multi-Agent Reinforcement Learning	Artificial Intelligence (cs.AI)	Yiqun Chen, Hangyu Mao, Tianle Zhang, Shiguang Wu, Bin Zhang, Jianye Hao, Dong Li, Bin Wang, Hongxing Chang
2210.08951	Approximating Continuous Convolutions for Deep Network Compression	Computer Vision and Pattern Recognition (cs.CV)	Theo W. Costain, Victor Adrian Prisacariu
2210.08988	Heterogeneous Feature Distillation Network for SAR Image Semantic Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Gao Mengyu, Dong Qiulei
2210.09022	Distilling Object Detectors With Global Knowledge	Computer Vision and Pattern Recognition (cs.CV)	Sanli Tang, Zhongyu Zhang, Zhanzhan Cheng, Jing Lu, Yunlu Xu, Yi Niu, Fan He
2210.09134	Principled Pruning of Bayesian Neural Networks through Variational Free Energy Minimization	Machine Learning (cs.LG)	Jim Beckers, Bart van Erp, Ziyue Zhao, Kirill Kondrashov, Bert de Vries
2210.09148	Pruning-based Topology Refinement of 3D Mesh using a 2D Alpha Mask	Computer Vision and Pattern Recognition (cs.CV)	Gaëtan Landreau, Mohamed Tamaazousti
2210.09223	oViT: An Accurate Second-Order Pruning Framework for Vision Transformers	Computer Vision and Pattern Recognition (cs.CV)	Denis Kuznedelev, Eldar Kurtic, Elias Frantar, Dan Alistarh
2210.09371	On Accelerated Perceptrons and Beyond	Machine Learning (cs.LG)	Guanghui Wang, Rafael Hanashiro, Etash Guha, Jacob Abernethy
2210.09609	SA-MLP: Distilling Graph Knowledge from GNNs into Structure-Aware MLP	Machine Learning (cs.LG)	Jie Chen, Shouzhen Chen, Mingyuan Bai, Junbin Gao, Junping Zhang, Jian Pu
2210.09668	On effects of Knowledge Distillation on Transfer Learning	Machine Learning (cs.LG)	Sushil Thapa
2210.09682	Accelerate Three-Dimensional Generative Adversarial Networks Using Fast Algorithm	Signal Processing (eess.SP)	Ziqi Su, Wendong Mao, Zhongfeng Wang, Jun Lin, Wenqiang Wang, Haitao Sun
2210.09922	Few-Shot Learning of Compact Models via Task-Specific Meta Distillation	Machine Learning (cs.LG)	Yong Wu, Shekhor Chanda, Mehrdad Hosseinzadeh, Zhi Liu, Yang Wang
2210.10246	Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction	Machine Learning (cs.LG)	Muralidhar Andoorveedu, Zhanda Zhu, Bojian Zheng, Gennady Pekhimenko
2210.10486	Cross-Modal Fusion Distillation for Fine-Grained Sketch-Based Image Retrieval	Computer Vision and Pattern Recognition (cs.CV)	Abhra Chaudhuri, Massimiliano Mancini, Yanbei Chen, Zeynep Akata, Anjan Dutta
2210.10495	Asymmetric Distillation Post-Segmentation Method for Image Anomaly Detection	Computer Vision and Pattern Recognition (cs.CV)	Peng Xing, Zechao Li
2210.10542	PoseGPT: Quantization-based 3D Human Motion Generation and Forecasting	Computer Vision and Pattern Recognition (cs.CV)	Thomas Lucas, Fabien Baradel, Philippe Weinzaepfel, Grégory Rogez
2210.10643	Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning	Machine Learning (cs.LG)	Linfeng Liu, Xu Han, Dawei Zhou, Li-Ping Liu
2210.10737	RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations	Machine Learning (cs.LG)	Zirui Liu, Shengyuan Chen, Kaixiong Zhou, Daochen Zha, Xiao Huang, Xia Hu
2210.10775	TOIST: Task Oriented Instance Segmentation Transformer with Noun-Pronoun Distillation	Computer Vision and Pattern Recognition (cs.CV)	Pengfei Li, Beiwen Tian, Yongliang Shi, Xiaoxue Chen, Hao Zhao, Guyue Zhou, Ya-Qin Zhang
2210.11094	Toward Multiple Specialty Learners for Explaining GNNs via Online Knowledge Distillation	Machine Learning (cs.LG)	Tien-Cuong Bui, Van-Duc Le, Wen-syan Li, Sang Kyun Cha
2210.11114	Pruning by Active Attention Manipulation	Computer Vision and Pattern Recognition (cs.CV)	Zahra Babaiee, Lucas Liebenwein, Ramin Hasani, Daniela Rus, Radu Grosu
2210.11708	Metric-guided Distillation: Distilling Knowledge from the Metric to Ranker and Retriever for Generative Commonsense Reasoning	Computation and Language (cs.CL)	Xingwei He, Yeyun Gong, A-Long Jin, Weizhen Qi, Hang Zhang, Jian Jiao, Bartuer Zhou, Biao Cheng, SM Yiu, Nan Duan
2210.11728	Distilling the Undistillable: Learning from a Nasty Teacher	Computer Vision and Pattern Recognition (cs.CV)	Surgan Jandial, Yash Khasbage, Arghya Pal, Vineeth N Balasubramanian, Balaji Krishnamurthy
2210.11768	Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation	Computation and Language (cs.CL)	Ziqi Wang, Yuexin Wu, Frederick Liu, Daogao Liu, Le Hou, Hongkun Yu, Jing Li, Heng Ji
2210.12067	Efficient Dataset Distillation Using Random Feature Approximation	Machine Learning (cs.LG)	Noel Loo, Ramin Hasani, Alexander Amini, Daniela Rus
2210.12427	Hard Gate Knowledge Distillation -- Leverage Calibration for Robust and Reliable Language Model	Computation and Language (cs.CL)	Dongkyu Lee, Zhiliang Tian, Yingxiu Zhao, Ka Chun Cheung, Nevin L. Zhang
2210.12538	Compressing multidimensional weather and climate data into neural networks	Machine Learning (cs.LG)	Langwen Huang, Torsten Hoefler
2210.12573	An Efficient Nonlinear Acceleration method that Exploits Symmetry of the Hessian	Machine Learning (cs.LG)	Huan He, Shifan Zhao, Ziyuan Tang, Joyce C Ho, Yousef Saad, Yuanzhe Xi
2210.12628	Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions	Artificial Intelligence (cs.AI)	Weirui Ye, Pieter Abbeel, Yang Gao
2210.12642	Accelerated Linearized Laplace Approximation for Bayesian Deep Learning	Machine Learning (cs.LG)	Zhijie Deng, Feng Zhou, Jun Zhu
2210.12782	Compressing Explicit Voxel Grid Representations: fast NeRFs become also small	Computer Vision and Pattern Recognition (cs.CV)	Chenxi Lola Deng, Enzo Tartaglione
2210.12787	Respecting Transfer Gap in Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yulei Niu, Long Chen, Chang Zhou, Hanwang Zhang
2210.12955	The Case for Accelerating BFT Protocols Using In-Network Ordering	Distributed, Parallel, and Cluster Computing (cs.DC)	Guangda Sun, Xin Zhe Khooi, Yunfan Li, Mingliang Jiang, Jialin Li
2210.12957	On the optimization and pruning for Bayesian deep learning	Machine Learning (cs.LG)	Xiongwen Ke, Yanan Fan
2210.13014	Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks	Machine Learning (cs.LG)	Chenxiao Yang, Qitian Wu, Junchi Yan
2210.13438	High Fidelity Neural Audio Compression	Audio and Speech Processing (eess.AS)	Alexandre Défossez, Jade Copet, Gabriel Synnaeve, Yossi Adi
2210.13457	Mixed Precision Quantization to Tackle Gradient Leakage Attacks in Federated Learning	Machine Learning (cs.LG)	Pretom Roy Ovi, Emon Dey, Nirmalya Roy, Aryya Gangopadhyay
2210.13738	Pruning's Effect on Generalization Through the Lens of Training and Regularization	Machine Learning (cs.LG)	Tian Jin, Michael Carbin, Daniel M. Roy, Jonathan Frankle, Gintare Karolina Dziugaite
2210.13743	Online Cross-Layer Knowledge Distillation on Graph Neural Networks with Deep Supervision	Machine Learning (cs.LG)	Jiongyu Guo, Defang Chen, Can Wang
2210.13769	GlobalFlowNet: Video Stabilization using Deep Distilled Global Motion Estimates	Computer Vision and Pattern Recognition (cs.CV)	Jerin Geo James (1), Devansh Jain (1), Ajit Rajwade (1) ((1) Indian Institute of Technology Bombay)
2210.13800	Referee: Reference-Free Sentence Summarization with Sharper Controllability through Symbolic Knowledge Distillation	Computation and Language (cs.CL)	Melanie Sclar, Peter West, Sachin Kumar, Yulia Tsvetkov, Yejin Choi
2210.13810	Toward domain generalized pruning by scoring out-of-distribution importance	Machine Learning (cs.LG)	Rizhao Cai, Haoliang Li, Alex Kot
2210.14215	In-context Reinforcement Learning with Algorithm Distillation	Machine Learning (cs.LG)	Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih
2210.14283	Accelerating Certified Robustness Training via Knowledge Transfer	Machine Learning (cs.LG)	Pratik Vaishnavi, Kevin Eykholt, Amir Rahmati
2210.14392	Zero-Shot Learning of a Conditional Generative Adversarial Network for Data-Free Network Quantization	Computer Vision and Pattern Recognition (cs.CV)	Yoojin Choi, Mostafa El-Khamy, Jungwon Lee
2210.14558	Compressing And Debiasing Vision-Language Pre-Trained Models for Visual Question Answering	Computer Vision and Pattern Recognition (cs.CV)	Qingyi Si, Yuanxin Liu, Zheng Lin, Peng Fu, Weiping Wang
2210.14560	Hierarchical Federated Learning with Momentum Acceleration in Multi-Tier Networks	Machine Learning (cs.LG)	Zhengjie Yang, Sen Fu, Wei Bao, Dong Yuan, Albert Y. Zomaya
2210.15071	Accelerated massive MIMO detector based on annealed underdamped Langevin dynamics	Signal Processing (eess.SP)	Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady, Ashutosh Sabharwal, Santiago Segarra
2210.15184	Too Brittle To Touch: Comparing the Stability of Quantization and Distillation Towards Developing Lightweight Low-Resource MT Models	Computation and Language (cs.CL)	Harshita Diddee, Sandipan Dandapat, Monojit Choudhury, Tanuja Ganu, Kalika Bali
2210.15274	Improved Feature Distillation via Projector Ensemble	Computer Vision and Pattern Recognition (cs.CV)	Yudong Chen, Sen Wang, Jiajun Liu, Xuwei Xu, Frank de Hoog, Zi Huang
2210.15563	Multimodal Transformer Distillation for Audio-Visual Synchronization	Computer Vision and Pattern Recognition (cs.CV)	Xuanjun Chen, Haibin Wu, Chung-Che Wang, Hung-yi Lee, Jyh-Shing Roger Jang
2210.15623	Neural Networks with Quantization Constraints	Machine Learning (cs.LG)	Ignacio Hounie, Juan Elenter, Alejandro Ribeiro
2210.15631	Exploring Effective Distillation of Self-Supervised Speech Models for Automatic Speech Recognition	Audio and Speech Processing (eess.AS)	Yujin Wang, Changli Tang, Ziyang Ma, Zhisheng Zheng, Xie Chen, Wei-Qiang Zhang
2210.15718	QUILL: Query Intent with Large Language Models using Retrieval Augmentation and Multi-stage Distillation	Computation and Language (cs.CL)	Krishna Srinivasan, Karthik Raman, Anupam Samanta, Lingrui Liao, Luca Bertelli, Mike Bendersky
2210.15809	Coverage-centric Coreset Selection for High Pruning Rates	Machine Learning (cs.LG)	Haizhong Zheng, Rui Liu, Fan Lai, Atul Prakash
2210.16103	Collaborative Multi-Teacher Knowledge Distillation for Learning Low Bit-width Deep Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Cuong Pham, Tuan Hoang, Thanh-Toan Do
2210.16402	GradSkip: Communication-Accelerated Local Gradient Methods with Better Computational Complexity	Machine Learning (cs.LG)	Artavazd Maranjyan, Mher Safaryan, Peter Richtárik
2210.16481	Accelerating RNN-T Training and Inference Using CTC guidance	Audio and Speech Processing (eess.AS)	Yongqiang Wang, Zhehuai Chen, Chengjian Zheng, Yu Zhang, Wei Han, Parisa Haghani
2210.16504	A pruning method based on the dissimilarity of angle among channels and filters	Computer Vision and Pattern Recognition (cs.CV)	Jiayi Yao, Ping Li, Xiatao Kang, Yuzhe Wang
2210.16611	Application of Knowledge Distillation to Multi-task Speech Representation Learning	Audio and Speech Processing (eess.AS)	Mine Kerpicci, Van Nguyen, Shuhua Zhang, Erik Visser
2210.16621	Empirical Evaluation of Post-Training Quantization Methods for Language Tasks	Computation and Language (cs.CL)	Ting Hu, Christoph Meinel, Haojin Yang
2210.16774	Dataset Distillation via Factorization	Computer Vision and Pattern Recognition (cs.CV)	Songhua Liu, Kai Wang, Xingyi Yang, Jingwen Ye, Xinchao Wang
2210.16987	Symbolic Distillation for Learned TCP Congestion Control	Machine Learning (cs.LG)	S P Sharan, Wenqing Zheng, Kuo-Feng Hsu, Jiarong Xing, Ang Chen, Zhangyang Wang
2210.17017	Blank Collapse: Compressing CTC emission for the faster decoding	Computation and Language (cs.CL)	Minkyu Jung, Ohhyeok Kwon, Seunghyun Seo, Soonshin Seo
2210.17047	Block-Wise Dynamic-Precision Neural Network Training Acceleration via Online Quantization Sensitivity Analytics	Machine Learning (cs.LG)	Ruoyang Liu, Chenhan Wei, Yixiong Yang, Wenxun Wang, Huazhong Yang, Yongpan Liu
2210.17051	Accelerating Carbon Capture and Storage Modeling using Fourier Neural Operators	Machine Learning (cs.LG)	Gege Wen, Zongyi Li, Qirui Long, Kamyar Azizzadenesheli, Anima Anandkumar, Sally M. Benson
2210.17113	Lightweight Neural Network with Knowledge Distillation for CSI Feedback	Signal Processing (eess.SP)	Yiming Cui, Jiajia Guo, Zheng Cao, Huaze Tang, Chao-Kai Wen, Shi Jin
2210.17168	SDCL: Self-Distillation Contrastive Learning for Chinese Spell Checking	Computation and Language (cs.CL)	Xiaotian Zhang, Hang Yan, Yu Sun, Xipeng Qiu
2210.17170	Efficient Document Retrieval by End-to-End Refining and Quantizing BERT Embedding with Contrastive Product Quantization	Information Retrieval (cs.IR)	Zexuan Qiu, Qinliang Su, Jianxing Yu, Shijing Si
2210.17223	Lita: Accelerating Distributed Training of Sparsely Activated Models	Distributed, Parallel, and Cluster Computing (cs.DC)	Jiamin Li, Yimin Jiang, Yibo Zhu, Cong Wang, Hong Xu
2210.17323	GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers	Machine Learning (cs.LG)	Elias Frantar, Saleh Ashkboos, Torsten Hoefler, Dan Alistarh
2210.17326	Model Compression for DNN-Based Text-Independent Speaker Verification Using Weight Quantization	Audio and Speech Processing (eess.AS)	Jingyu Li, Zhaoyang Zhang, Jiong Wang, Tan Lee
2210.17357	L-GreCo: An Efficient and General Framework for Layerwise-Adaptive Gradient Compression	Machine Learning (cs.LG)	Mohammadreza Alimohammadi, Ilia Markov, Elias Frantar, Dan Alistarh
2210.17416	Efficient Similarity-based Passive Filter Pruning for Compressing CNNs	Computer Vision and Pattern Recognition (cs.CV)	Arshdeep Singh, Mark D. Plumbley
2211.00188	Adaptive Compression for Communication-Efficient Distributed Training	Machine Learning (cs.LG)	Maksim Makarenko, Elnur Gasanov, Rustem Islamov, Abdurakhmon Sadiev, Peter Richtarik
2211.00218	Pixel-Wise Contrastive Distillation	Computer Vision and Pattern Recognition (cs.CV)	Junqiang Huang, Zichao Guo
2211.00239	ARDIR: Improving Robustness using Knowledge Distillation of Internal Representation	Machine Learning (cs.LG)	Tomokatsu Takahashi, Masanori Yamada, Yuuki Yamanaka, Tomoya Yamashita
2211.00288	Self-supervised Character-to-Character Distillation	Computer Vision and Pattern Recognition (cs.CV)	Tongkun Guan, Wei Shen
2211.00310	SADT: Combining Sharpness-Aware Minimization with Self-Distillation for Improved Model Generalization	Machine Learning (cs.LG)	Masud An-Nur Islam Fahim, Jani Boutellier
2211.00466	Recognition of Defective Mineral Wool Using Pruned ResNet Models	Computer Vision and Pattern Recognition (cs.CV)	Mehdi Rafiei, Dat Thanh Tran, Alexandros Iosifidis
2211.00508	Predicting Multi-Codebook Vector Quantization Indexes for Knowledge Distillation	Audio and Speech Processing (eess.AS)	Liyong Guo, Xiaoyu Yang, Quandong Wang, Yuxiang Kong, Zengwei Yao, Fan Cui, Fangjun Kuang, Wei Kang, Long Lin, Mingshuang Luo, Piotr Zelasko, Daniel Povey
2211.00549	No-audio speaking status detection in crowded settings via visual pose-based filtering and wearable acceleration	Computer Vision and Pattern Recognition (cs.CV)	Jose Vargas-Quiros, Laura Cabrera-Quiros, Hayley Hung
2211.00683	Reduce, Reuse, Recycle: Improving Training Efficiency with Distillation	Machine Learning (cs.LG)	Cody Blakeney, Jessica Zosa Forde, Jonathan Frankle, Ziliang Zong, Matthew L. Leavitt
2211.00734	On the Interaction Between Differential Privacy and Gradient Compression in Deep Learning	Machine Learning (cs.LG)	Jimmy Lin
2211.00748	Maximum Likelihood Distillation for Robust Modulation Classification	Machine Learning (cs.LG)	Javier Maroto, Gérôme Bovet, Pascal Frossard
2211.00856	Deep Virtual-to-Real Distillation for Pedestrian Crossing Prediction	Computer Vision and Pattern Recognition (cs.CV)	Jie Bai, Xin Fang, Jianwu Fang, Jianru Xue, Changwei Yuan
2211.00889	Accelerating Parallel Stochastic Gradient Descent via Non-blocking Mini-batches	Machine Learning (cs.LG)	Haoze He, Parijat Dube
2211.01071	Gradient Knowledge Distillation for Pre-trained Language Models	Computation and Language (cs.CL)	Lean Wang, Lei Li, Xu Sun
2211.01200	Multi-level Distillation of Semantic Knowledge for Pre-training Multilingual Language Model	Computation and Language (cs.CL)	Mingqi Li, Fei Ding, Dan Zhang, Long Cheng, Hongxin Hu, Feng Luo
2211.01311	Distill and Collect for Semi-Supervised Temporal Action Segmentation	Computer Vision and Pattern Recognition (cs.CV)	Sovan Biswas, Anthony Rhodes, Ramesh Manuvinakurike, Giuseppe Raffa, Richard Beckwith
2211.01342	Fine-grained Human Activity Recognition Using Virtual On-body Acceleration Data	Computer Vision and Pattern Recognition (cs.CV)	Zikang Leng, Yash Jain, Hyeokhyen Kwon, Thomas Plötz
2211.01814	Self Similarity Matrix based CNN Filter Pruning	Machine Learning (cs.LG)	S Rakshith, Jayesh Rajkumar Vachhani, Sourabh Vasant Gothe, Rishabh Khurana
2211.01957	Sub-network Multi-objective Evolutionary Algorithm for Filter Pruning	Neural and Evolutionary Computing (cs.NE)	Xuhua Li, Weize Sun, Lei Huang, Shaowu Chen
2211.02012	Optimal Compression for Minimizing Classification Error Probability: an Information-Theoretic Approach	Signal Processing (eess.SP)	Jingchao Gao, Ao Tang, Weiyu Xu
2211.02206	Soft Masking for Cost-Constrained Channel Pruning	Computer Vision and Pattern Recognition (cs.CV)	Ryan Humble, Maying Shen, Jorge Albericio Latorre, Eric Darve1, Jose M. Alvarez
2211.02332	Once-for-All Sequence Compression for Self-Supervised Speech Models	Computation and Language (cs.CL)	Hsuan-Jui Chen, Yen Meng, Hung-yi Lee
2211.02632	Fault Diagnosis for Power Electronics Converters based on Deep Feedforward Network and Wavelet Compression	Signal Processing (eess.SP)	Lei Kou, Chuang Liu, Guowei Cai, Zhe Zhang
2211.02638	A Knowledge Distillation Framework For Enhancing Ear-EEG Based Sleep Staging With Scalp-EEG Data	Signal Processing (eess.SP)	Mithunjha Anandakumar, Jathurshan Pradeepkumar, Simon L. Kappel, Chamira U. S. Edussooriya, Anjula C. De Silva
2211.02720	Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks	Machine Learning (cs.LG)	Ryien Hosseini, Filippo Simini, Austin Clyde, Arvind Ramanathan
2211.02738	Intriguing Properties of Compression on Multilingual Models	Computation and Language (cs.CL)	Kelechi Ogueji, Orevaoghene Ahia, Gbemileke Onilude, Sebastian Gehrmann, Sara Hooker, Julia Kreutzer
2211.02944	Breaking the trade-off in personalized speech enhancement with cross-task knowledge distillation	Audio and Speech Processing (eess.AS)	Hassan Taherian, Sefik Emre Eskimez, Takuya Yoshioka
2211.03000	Distilling Representations from GAN Generator via Squeeze and Span	Computer Vision and Pattern Recognition (cs.CV)	Yu Yang, Xiaotian Cheng, Chang Liu, Hakan Bilen, Xiangyang Ji
2211.03946	Understanding the Role of Mixup in Knowledge Distillation: An Empirical Study	Computer Vision and Pattern Recognition (cs.CV)	Hongjun Choi, Eun Som Jeon, Ankita Shukla, Pavan Turaga
2211.03972	Quantization-Based Optimization: Alternative Stochastic Approximation of Global Optimization	Machine Learning (cs.LG)	Jinwuk Seok, Chang Sik Cho
2211.04031	Hilbert Distillation for Cross-Dimensionality Networks	Computer Vision and Pattern Recognition (cs.CV)	Dian Qin, Haishuai Wang, Zhe Liu, Hongjia Xu, Sheng Zhou, Jiajun Bu
2211.04168	Pushing the limits of self-supervised speaker verification using regularized distillation framework	Audio and Speech Processing (eess.AS)	Yafeng Chen, Siqi Zheng, Hui Wang, Luyao Cheng, Qian Chen
2211.04257	Toward Human-AI Co-creation to Accelerate Material Discovery	Machine Learning (cs.LG)	Dmitry Zubarev, Carlos Raoni Mendes, Emilio Vital Brazil, Renato Cerqueira, Kristin Schmidt, Vinicius Segura, Juliana Jansen Ferreira, Dan Sanders
2211.04515	QuantPipe: Applying Adaptive Post-Training Quantization for Distributed Transformer Pipelines in Dynamic Edge Environments	Distributed, Parallel, and Cluster Computing (cs.DC)	Haonan Wang, Connor Imes, Souvik Kundu, Peter A. Beerel, Stephen P. Crago, John Paul Walters
2211.04742	Knowledge Distillation for Federated Learning: a Practical Guide	Machine Learning (cs.LG)	Alessio Mora, Irene Tenison, Paolo Bellavista, Irina Rish
2211.04934	DoSA : A System to Accelerate Annotations on Business Documents with Human-in-the-Loop	Computation and Language (cs.CL)	Neelesh K Shukla, Msp Raja, Raghu Katikeri, Amit Vaid
2211.04973	Accelerating Adversarial Perturbation by 50% with Semi-backward Propagation	Machine Learning (cs.LG)	Zhiqi Bu
2211.05109	ViTALiTy: Unifying Low-rank and Sparse Approximation for Vision Transformer Acceleration with a Linear Taylor Attention	Computer Vision and Pattern Recognition (cs.CV)	Jyotikrishna Dass, Shang Wu, Huihong Shi, Chaojian Li, Zhifan Ye, Zhongfeng Wang, Yingyan Lin
2211.05488	ClassPruning: Speed Up Image Restoration Networks by Dynamic N:M Pruning	Computer Vision and Pattern Recognition (cs.CV)	Yang Zhou, Yuda Song, Hui Qian, Xin Du
2211.05610	BERT on a Data Diet: Finding Important Examples by Gradient-Based Pruning	Computation and Language (cs.CL)	Mohsen Fayyaz, Ehsan Aghazadeh, Ali Modarressi, Mohammad Taher Pilehvar, Yadollah Yaghoobzadeh, Samira Ebrahimi Kahou
2211.05805	Impact of Video Compression on the Performance of Object Detection Systems for Surveillance Applications	Computer Vision and Pattern Recognition (cs.CV)	Michael O'Byrne, Vibhoothi, Mark Sugrue, Anil Kokaram
2211.06018	MDFlow: Unsupervised Optical Flow Learning by Reliable Mutual Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Lingtong Kong, Jie Yang
2211.06059	PILE: Pairwise Iterative Logits Ensemble for Multi-Teacher Labeled Distillation	Information Retrieval (cs.IR)	Lianshang Cai, Linhao Zhang, Dehong Ma, Jun Fan, Daiting Shi, Yi Wu, Zhicong Cheng, Simiu Gu, Dawei Yin
2211.06143	FAN-Trans: Online Knowledge Distillation for Facial Action Unit Detection	Computer Vision and Pattern Recognition (cs.CV)	Jing Yang, Jie Shen, Yiming Lin, Yordan Hristov, Maja Pantic
2211.06196	Improving Factual Consistency in Summarization with Compression-Based Post-Editing	Computation and Language (cs.CL)	Alexander R. Fabbri, Prafulla Kumar Choubey, Jesse Vig, Chien-Sheng Wu, Caiming Xiong
2211.06581	Variational Augmentation for Enhancing Historical Document Image Binarization	Computer Vision and Pattern Recognition (cs.CV)	Avirup Dey, Nibaran Das, Mita Nasipuri
2211.06689	TINC: Tree-structured Implicit Neural Compression	Computer Vision and Pattern Recognition (cs.CV)	Runzhao Yang, Tingxiong Xiao, Yuxiao Cheng, Jinli Suo, Qionghai Dai
2211.06739	MixBin: Towards Budgeted Binarization	Computer Vision and Pattern Recognition (cs.CV)	Udbhav Bamba, Neeraj Anand, Dilip K. Prasad, Deepak K. Gupta
2211.06797	SMR: Satisfied Machine Ratio Modeling for Machine Recognition-Oriented Image and Video Compression	Computer Vision and Pattern Recognition (cs.CV)	Qi Zhang, Shanshe Wang, Xinfeng Zhang, Chuanmin Jia, Jingshan Pan, Siwei Ma, Wen Gao
2211.06816	Long-Range Zero-Shot Generative Deep Network Quantization	Computer Vision and Pattern Recognition (cs.CV)	Yan Luo, Yangcheng Gao, Zhao Zhang, Haijun Zhang, Mingliang Xu, Meng Wang
2211.07171	Cross-Modality Knowledge Distillation Network for Monocular 3D Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Yu Hong, Hang Dai, Yong Ding
2211.07566	Self-distillation with Online Diffusion on Batch Manifolds Improves Deep Metric Learning	Computer Vision and Pattern Recognition (cs.CV)	Zelong Zeng, Fan Yang, Hong Liu, Shin'ichi Satoh
2211.07647	An Interpretable Neuron Embedding for Static Knowledge Distillation	Machine Learning (cs.LG)	Wei Han, Yangqiming Wang, Christian Böhm, Junming Shao
2211.08071	Knowledge Distillation for Detection Transformer with Consistent Distillation Points Sampling	Computer Vision and Pattern Recognition (cs.CV)	Yu Wang, Xin Li, Shengzhao Wen, Fukui Yang, Wanping Zhang, Gang Zhang, Haocheng Feng, Junyu Han, Errui Ding
2211.08106	Instance-aware Model Ensemble With Distillation For Unsupervised Domain Adaptation	Computer Vision and Pattern Recognition (cs.CV)	Weimin Wu, Jiayuan Fan, Tao Chen, Hancheng Ye, Bo Zhang, Baopu Li
2211.08161	Exploring the Joint Use of Rehearsal and Knowledge Distillation in Continual Learning for Spoken Language Understanding	Audio and Speech Processing (eess.AS)	Umberto Cappellazzo, Daniele Falavigna, Alessio Brutti
2211.08339	Pruning Very Deep Neural Network Channels for Efficient Inference	Computer Vision and Pattern Recognition (cs.CV)	Yihui He
2211.08398	Structured Knowledge Distillation Towards Efficient and Compact Multi-View 3D Detection	Computer Vision and Pattern Recognition (cs.CV)	Linfeng Zhang, Yukang Shi, Hung-Shuo Tai, Zhipeng Zhang, Yuan He, Ke Wang, Kaisheng Ma
2211.08544	Exploiting the Partly Scratch-off Lottery Ticket for Quantization-Aware Training	Computer Vision and Pattern Recognition (cs.CV)	Yunshan Zhong, Mingbao Lin, Yuxin Zhang, Gongrui Nan, Fei Chao, Rongrong Ji
2211.09320	Improving Federated Learning Communication Efficiency with Global Momentum Fusion for Gradient Compression Schemes	Distributed, Parallel, and Cluster Computing (cs.DC)	Chun-Chih Kuo, Ted Tsei Kuo, Chia-Yu Lin
2211.09386	BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Zehui Chen, Zhenyu Li, Shiquan Zhang, Liangji Fang, Qinhong Jiang, Feng Zhao
2211.09643	CPT-V: A Contrastive Approach to Post-Training Quantization of Vision Transformers	Computer Vision and Pattern Recognition (cs.CV)	Natalia Frumkin, Dibakar Gope, Diana Marculescu
2211.09740	Sub-Graph Learning for Spatiotemporal Forecasting via Knowledge Distillation	Machine Learning (cs.LG)	Mehrtash Mehrabi, Yingxue Zhang
2211.09744	Zero-Shot Dynamic Quantization for Transformer Inference	Computation and Language (cs.CL)	Yousef El-Kurdi, Jerry Quinn, Avirup Sil
2211.09768	D$^3$ETR: Decoder Distillation for Detection Transformer	Computer Vision and Pattern Recognition (cs.CV)	Xiaokang Chen, Jiahui Chen, Yan Liu, Gang Zeng
2211.09894	Supervised Feature Compression based on Counterfactual Analysis	Machine Learning (cs.LG)	Veronica Piccialli, Dolores Romero Morales, Cecilia Salvatore
2211.09949	Compressing Transformer-based self-supervised models for speech processing	Computation and Language (cs.CL)	Tzu-Quan Lin, Tsung-Huan Yang, Chun-Yao Chang, Kuang-Ming Chen, Tzu-hsun Feng, Hung-yi Lee, Hao Tang
2211.10025	Multiuser-MIMO Systems Using Comparator Network-Aided Receivers With 1-Bit Quantization	Signal Processing (eess.SP)	Ana Beatriz L. B. Fernandes, Zhichao Shao, Lukas T. N. Landau, Rodrigo C. de Lamare
2211.10155	Structured Pruning Adapters	Computer Vision and Pattern Recognition (cs.CV)	Lukas Hedegaard, Aman Alok, Juby Jose, Alexandros Iosifidis
2211.10156	DETRDistill: A Universal Knowledge Distillation Framework for DETR-families	Computer Vision and Pattern Recognition (cs.CV)	Jiahao Chang, Shuo Wang, Guangkai Xu, Zehui Chen, Chenhongyi Yang, Feng Zhao
2211.10285	A Fair Loss Function for Network Pruning	Machine Learning (cs.LG)	Robbie Meyer, Alexander Wong
2211.10438	SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models	Computation and Language (cs.CL)	Guangxuan Xiao, Ji Lin, Mickael Seznec, Julien Demouth, Song Han
2211.10526	Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference	Computer Vision and Pattern Recognition (cs.CV)	Haoran You, Yunyang Xiong, Xiaoliang Dai, Bichen Wu, Peizhao Zhang, Haoqi Fan, Peter Vajda, Yingyan Lin
2211.10586	Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory	Computer Vision and Pattern Recognition (cs.CV)	Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh
2211.10725	Intelligence Processing Units Accelerate Neuromorphic Learning	Machine Learning (cs.LG)	Pao-Sheng Vincent Sun, Alexander Titterton, Anjlee Gopiani, Tim Santos, Arindam Basu, Wei D. Lu, Jason K. Eshraghian
2211.10938	AI-KD: Adversarial learning and Implicit regularization for self-Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Hyungmin Kim, Sungho Suh, Sunghyun Baek, Daehwan Kim, Daun Jeong, Hansang Cho, Junmo Kim
2211.11004	Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation	Machine Learning (cs.LG)	Jiawei Du, Yidi Jiang, Vincent Y. F. Tan, Joey Tianyi Zhou, Haizhou Li
2211.11014	Understanding and Improving Knowledge Distillation for Quantization-Aware Training of Large Transformer Encoders	Computation and Language (cs.CL)	Minsoo Kim, Sihwa Lee, Sukjin Hong, Du-Seong Chang, Jungwook Choi
2211.11152	You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model	Computer Vision and Pattern Recognition (cs.CV)	Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu
2211.11159	Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge Distillation	Information Retrieval (cs.IR)	Zhen Tian, Ting Bai, Zibin Zhang, Zhiyuan Xu, Kangyi Lin, Ji-Rong Wen, Wayne Xin Zhao
2211.11300	Multi-Level Knowledge Distillation for Out-of-Distribution Detection in Text	Computation and Language (cs.CL)	Qianhui Wu, Huiqiang Jiang, Haonan Yin, Borje F. Karlsson, Chin-Yew Lin
2211.11355	Blind Knowledge Distillation for Robust Image Classification	Computer Vision and Pattern Recognition (cs.CV)	Timo Kaiser, Lukas Ehmann, Christoph Reinders, Bodo Rosenhahn
2211.11397	Learning Low-Rank Representations for Model Compression	Computer Vision and Pattern Recognition (cs.CV)	Zezhou Zhu, Yucong Zhou, Zhao Zhong
2211.11647	Benchmarking Edge Computing Devices for Grape Bunches and Trunks Detection using Accelerated Object Detection Single Shot MultiBox Deep Learning Models	Computer Vision and Pattern Recognition (cs.CV)	Sandro Costa Magalhães, Filipe Neves Santos, Pedro Machado, António Paulo Moreira, Jorge Dias
2211.11738	SPARF: Neural Radiance Fields from Sparse and Noisy Poses	Computer Vision and Pattern Recognition (cs.CV)	Prune Truong, Marie-Julie Rakotosaona, Fabian Manhardt, Federico Tombari
2211.12020	PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design	Machine Learning (cs.LG)	Alexandre Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García, David Rolnick
2211.12039	Accelerating Diffusion Sampling with Classifier-based Feature Distillation	Computer Vision and Pattern Recognition (cs.CV)	Wujie Sun, Defang Chen, Can Wang, Deshi Ye, Yan Feng, Chun Chen
2211.12109	Video compression dataset and benchmark of learning-based video-quality metrics	Computer Vision and Pattern Recognition (cs.CV)	Anastasia Antsiferova, Sergey Lavrushkin, Maksim Smirnov, Alexander Gushchin, Dmitriy Vatolin, Dmitriy Kulikov
2211.12219	Adaptive Sparse Structure Development with Pruning and Regeneration for Spiking Neural Networks	Neural and Evolutionary Computing (cs.NE)	Bing Han, Feifei Zhao, Yi Zeng, Wenxuan Pan
2211.12419	Accuracy Prediction for NAS Acceleration using Feature Selection and Extrapolation	Machine Learning (cs.LG)	Tal Hakim
2211.12423	On Narrative Information and the Distillation of Stories	Computation and Language (cs.CL)	Dylan R. Ashley, Vincent Herrmann, Zachary Friggstad, Jürgen Schmidhuber
2211.12551	Sparse Probabilistic Circuits via Pruning and Growing	Machine Learning (cs.LG)	Meihua Dang, Anji Liu, Guy Van den Broeck
2211.12631	A Generic Approach for Reproducible Model Distillation	Machine Learning (stat.ML)	Yunzhe Zhou, Peiru Xu, Giles Hooker
2211.12714	Developmental Plasticity-inspired Adaptive Pruning for Deep Spiking and Artificial Neural Networks	Neural and Evolutionary Computing (cs.NE)	Bing Han, Feifei Zhao, Yi Zeng, Guobin Shen
2211.12715	Embedding Compression for Text Classification Using Dictionary Screening	Computation and Language (cs.CL)	Jing Zhou, Xinru Jing, Muyu Liu, Hansheng Wang
2211.13125	EEG aided boosting of single-lead ECG based sleep staging with Deep Knowledge Distillation	Signal Processing (eess.SP)	Vaibhav Joshi, Sricharan V, Preejith SP, Mohanasankar Sivaprakasam
2211.13133	Structural Knowledge Distillation for Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Philip de Rijk, Lukas Schneider, Marius Cordts, Dariu M. Gavrila
2211.13137	Pruned Lightweight Encoders for Computer Vision	Computer Vision and Pattern Recognition (cs.CV)	Jakub Žádník, Markku Mäkitalo, Pekka Jääskeläinen
2211.13264	Distilling Knowledge from Self-Supervised Teacher by Embedding Graph Alignment	Computer Vision and Pattern Recognition (cs.CV)	Yuchen Ma, Yanbei Chen, Zeynep Akata
2211.13356	Vector Quantization Methods for Access Point Placement in Cell-Free Massive MIMO Systems	Signal Processing (eess.SP)	Govind R. Gopal, Bhaskar D. Rao
2211.13479	Alternating Deep Low Rank Approach for Exponential Function Reconstruction and Its Biomedical Magnetic Resonance Applications	Signal Processing (eess.SP)	Yihui Huang, Zi Wang, Xinlin Zhang, Jian Cao, Zhangren Tu, Di Guo, Xiaobo Qu
2211.13609	PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization	Machine Learning (cs.LG)	Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew Gordon Wilson
2211.13708	Reduction Algorithms for Persistence Diagrams of Networks: CoralTDA and PrunIT	Machine Learning (cs.LG)	Cuneyt Gurcan Akcora, Murat Kantarcioglu, Yulia R. Gel, Baris Coskunuzer
2211.13745	Attention-based Feature Compression for CNN Inference Offloading in Edge Computing	Computer Vision and Pattern Recognition (cs.CV)	Nan Li, Alexandros Iosifidis, Qi Zhang
2211.13769	On designing light-weight object trackers through network pruning: Use CNNs or transformers?	Computer Vision and Pattern Recognition (cs.CV)	Saksham Aggarwal, Taneesh Gupta, Pawan Kumar Sahu, Arnav Chavan, Rishabh Tiwari, Dilip K. Prasad, Deepak K. Gupta
2211.13778	Design and Prototyping Distributed CNN Inference Acceleration in Edge Computing	Computer Vision and Pattern Recognition (cs.CV)	Zhongtian Dong, Nan Li, Alexandros Iosifidis, Qi Zhang
2211.13853	Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry	Machine Learning (cs.LG)	Hatem Helal, Jesun Firoz, Jenna Bilbrey, Mario Michael Krell, Tom Murray, Ang Li, Sotiris Xantheas, Sutanay Choudhury
2211.13929	XKD: Cross-modal Knowledge Distillation with Domain Alignment for Video Representation Learning	Computer Vision and Pattern Recognition (cs.CV)	Pritam Sarkar, Ali Etemad
2211.14036	Privileged Prior Information Distillation for Image Matting	Computer Vision and Pattern Recognition (cs.CV)	Cheng Lyu, Jiake Xie, Bo Xu, Cheng Lu, Han Huang, Xin Huang, Ming Wu, Chuang Zhang, Yong Tang
2211.14054	CAD2Render: A Modular Toolkit for GPU-accelerated Photorealistic Synthetic Data Generation for the Manufacturing Industry	Computer Vision and Pattern Recognition (cs.CV)	Steven Moonen, Bram Vanherle, Joris de Hoog, Taoufik Bourgana, Abdellatif Bey-Temsamani, Nick Michiels
2211.14058	Cross-Domain Ensemble Distillation for Domain Generalization	Computer Vision and Pattern Recognition (cs.CV)	Kyungmoon Lee, Sungyeon Kim, Suha Kwak
2211.14241	Look Around and Refer: 2D Synthetic Semantics Knowledge Distillation for 3D Visual Grounding	Computer Vision and Pattern Recognition (cs.CV)	Eslam Mohamed Bakr, Yasmeen Alsaedy, Mohamed Elhoseiny
2211.14292	Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression	Machine Learning (stat.ML)	Xiaoyun Li, Ping Li
2211.14296	A System for Morphology-Task Generalization via Unified Representation and Behavior Distillation	Machine Learning (cs.LG)	Hiroki Furuta, Yusuke Iwasawa, Yutaka Matsuo, Shixiang Shane Gu
2211.14363	Homology-constrained vector quantization entropy regularizer	Machine Learning (cs.LG)	Ivan Volkov
2211.14466	SKDBERT: Compressing BERT via Stochastic Knowledge Distillation	Computation and Language (cs.CL)	Zixiang Ding, Guoqing Jiang, Shuai Zhang, Lin Guo, Wei Lin
2211.14729	Unbiased Knowledge Distillation for Recommendation	Information Retrieval (cs.IR)	Gang Chen, Jiawei Chen, Fuli Feng, Sheng Zhou, Xiangnan He
2211.14742	Dynamic Feature Pruning and Consolidation for Occluded Person Re-Identification	Computer Vision and Pattern Recognition (cs.CV)	Yuteng Ye, Hang Zhou, Junqing Yu, Qiang Hu, Wei Yang
2211.14773	Class-aware Information for Logit-based Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Shuoxi Zhang, Hanpeng Liu, John E. Hopcroft, Kun He
2211.14920	EPIK: Eliminating multi-model Pipelines with Knowledge-distillation	Computation and Language (cs.CL)	Bhavesh Laddagiri, Yash Raj, Anshuman Dash
2211.14928	Class-based Quantization for Neural Networks	Machine Learning (cs.LG)	Wenhao Sun, Grace Li Zhang, Huaxi Gu, Bing Li, Ulf Schlichtmann
2211.15023	AcceRL: Policy Acceleration Framework for Deep Reinforcement Learning	Machine Learning (cs.LG)	Hongjie Zhang
2211.15075	Inter-KD: Intermediate Knowledge Distillation for CTC-Based Automatic Speech Recognition	Audio and Speech Processing (eess.AS)	Ji Won Yoon, Beom Jun Woo, Sunghwan Ahn, Hyeonseung Lee, Nam Soo Kim
2211.15597	Lightning Fast Video Anomaly Detection via Adversarial Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Nicolae-Catalin Ristea, Florinel-Alin Croitoru, Dana Dascalescu, Radu Tudor Ionescu, Fahad Shahbaz Khan, Mubarak Shah
2211.15736	Post-training Quantization on Diffusion Models	Computer Vision and Pattern Recognition (cs.CV)	Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, Yan Yan
2211.15770	Accelerated Nonnegative Tensor Completion via Integer Programming	Machine Learning (cs.LG)	Wenhao Pan, Anil Aswani, Chen Chen
2211.15774	Decentralized Learning with Multi-Headed Distillation	Machine Learning (cs.LG)	Andrey Zhmoginov, Mark Sandler, Nolan Miller, Gus Kristiansen, Max Vladymyrov
2211.15927	Compressing Cross-Lingual Multi-Task Models at Qualtrics	Computation and Language (cs.CL)	Daniel Campos, Daniel Perry, Samir Joshi, Yashmeet Gambhir, Wei Du, Zhengzheng Xing, Aaron Colak
2211.15951	Feature-based Adaptive Contrastive Distillation for Efficient Single Image Super-Resolution	Computer Vision and Pattern Recognition (cs.CV)	HyeonCheol Moon, JinWoo Jeong, SungJei Kim
2211.15977	One is All: Bridging the Gap Between Neural Radiance Fields Architectures with Progressive Volume Distillation	Computer Vision and Pattern Recognition (cs.CV)	Shuangkang Fang, Weixin Xu, Heng Wang, Yi Yang, Yufeng Wang, Shuchang Zhou
2211.16056	NoisyQuant: Noisy Bias-Enhanced Post-Training Activation Quantization for Vision Transformers	Computer Vision and Pattern Recognition (cs.CV)	Yijiang Liu, Huanrui Yang, Zhen Dong, Kurt Keutzer, Li Du, Shanghang Zhang
2211.16098	Three-stage binarization of color document images based on discrete wavelet transform and generative adversarial networks	Computer Vision and Pattern Recognition (cs.CV)	Yu-Shian Lin, Rui-Yang Ju, Chih-Chia Chen, Ting-Yu Lin, Jen-Shiun Chiang
2211.16187	Quantization-aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks	Machine Learning (cs.LG)	Mathias Lechner, Đorđe Žikelić, Krishnendu Chatterjee, Thomas A. Henzinger, Daniela Rus
2211.16231	Curriculum Temperature for Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Zheng Li, Xiang Li, Lingfeng Yang, Borui Zhao, Renjie Song, Lei Luo, Jun Li, Jian Yang
2211.16386	Compressing Volumetric Radiance Fields to 1 MB	Computer Vision and Pattern Recognition (cs.CV)	Lingzhi Li, Zhen Shen, Zhongshu Wang, Li Shen, Liefeng Bo
2211.16712	Coordinating Cross-modal Distillation for Molecular Property Prediction	Machine Learning (cs.LG)	Hao Zhang, Nan Zhang, Ruixin Zhang, Lei Shen, Yingyi Zhang, Meng Liu
2211.16779	Attention-based Depth Distillation with 3D-Aware Positional Encoding for Monocular 3D Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Zizhang Wu, Yunzhe Wu, Jian Pu, Xianzhi Li, Xiaoquan Wang
2211.16912	Quadapter: Adapter for GPT-2 Quantization	Machine Learning (cs.LG)	Minseop Park, Jaeseong You, Markus Nagel, Simyung Chang
2211.17059	Hint-dynamic Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Yiyang Liu, Chenxin Li, Xiaotong Tu, Xinghao Ding, Yue Huang
2211.17201	ExtremeBERT: A Toolkit for Accelerating Pretraining of Customized BERT	Computation and Language (cs.CL)	Rui Pan, Shizhe Diao, Jianlin Chen, Tong Zhang
2212.00193	Distilling Multi-Step Reasoning Capabilities of Large Language Models into Smaller Models via Semantic Decompositions	Machine Learning (cs.LG)	Kumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan
2212.00223	Biomedical NER for the Enterprise with Distillated BERN2 and the Kazu Framework	Computation and Language (cs.CL)	Wonjin Yoon, Richard Jackson, Elliot Ford, Vladimir Poroshin, Jaewoo Kang
2212.00291	The Effect of Data Dimensionality on Neural Network Prunability	Machine Learning (cs.LG)	Zachary Ankner, Alex Renda, Gintare Karolina Dziugaite, Jonathan Frankle, Tian Jin
2212.00623	BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for BEV 3D Object Detection	Computer Vision and Pattern Recognition (cs.CV)	Jianing Li, Ming Lu, Jiaming Liu, Yandong Guo, Li Du, Shanghang Zhang
2212.00792	SparseFusion: Distilling View-conditioned Diffusion for 3D Reconstruction	Computer Vision and Pattern Recognition (cs.CV)	Zhizhuo Zhou, Shubham Tulsiani
2212.00937	StructVPR: Distill Structural Knowledge with Weighting Samples for Visual Place Recognition	Computer Vision and Pattern Recognition (cs.CV)	Yanqing Shen, Sanping Zhou, Jingwen Fu, Ruotong Wang, Shitao Chen, Nanning Zheng
2212.01012	Injecting Spatial Information for Monaural Speech Enhancement via Knowledge Distillation	Audio and Speech Processing (eess.AS)	Xinmeng Xu, Weiping Tu, Yuhong Yang
2212.01016	Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling	Machine Learning (cs.LG)	Jiaxin Zhang, Sirui Bi, Victor Fung
2212.01348	Predict-and-Critic: Accelerated End-to-End Predictive Control for Cloud Computing through Reinforcement Learning	Machine Learning (cs.LG)	Kaustubh Sridhar, Vikramank Singh, Balakrishnan Narayanaswamy, Abishek Sankararaman
2212.01386	Convolution, aggregation and attention based deep neural networks for accelerating simulations in mechanics	Machine Learning (cs.LG)	Saurabh Deshpande, Raúl I. Sosa, Stéphane P.A. Bordas, Jakub Lengiewicz
2212.01575	Multi-view deep learning based molecule design and structural optimization accelerates the SARS-CoV-2 inhibitor discovery	Machine Learning (cs.LG)	Chao Pang, Yu Wang, Yi Jiang, Ruheng Wang, Ran Su, Leyi Wei
2212.01593	Make RepVGG Greater Again: A Quantization-aware Approach	Computer Vision and Pattern Recognition (cs.CV)	Xiangxiang Chu, Liang Li, Bo Zhang
2212.01959	INGeo: Accelerating Instant Neural Scene Reconstruction with Noisy Geometry Priors	Computer Vision and Pattern Recognition (cs.CV)	Chaojian Li, Bichen Wu, Albert Pumarola, Peizhao Zhang, Yingyan Lin, Peter Vajda
2212.01977	FedTiny: Pruned Federated Learning Towards Specialized Tiny Models	Machine Learning (cs.LG)	Hong Huang, Lan Zhang, Chaoyue Sun, Ruogu Fang, Xiaoyong Yuan, Dapeng Wu
2212.02006	HierarchyFL: Heterogeneous Federated Learning via Hierarchical Self-Distillation	Machine Learning (cs.LG)	Jun Xia, Yi Zhang, Zhihao Yue, Ming Hu, Xian Wei, Mingsong Chen
2212.02190	L2SR: Learning to Sample and Reconstruct for Accelerated MRI	Computer Vision and Pattern Recognition (cs.CV)	Pu Yang, Bin Dong
2212.02196	FedUKD: Federated UNet Model with Knowledge Distillation for Land Use Classification from Satellite and Street Views	Computer Vision and Pattern Recognition (cs.CV)	Renuga Kanagavelu, Kinshuk Dua, Pratik Garai, Susan Elias, Neha Thomas, Simon Elias, Qingsong Wei, Goh Siow Mong Rick, Liu Yong
2212.02303	Lossy Compression for Robust Unsupervised Time-Series Anomaly Detection	Machine Learning (cs.LG)	Christopher P. Ley, Jorge F. Silva
2212.02304	Matching DNN Compression and Cooperative Training with Resources and Data Availability	Machine Learning (cs.LG)	Francesco Malandrino, Giuseppe Di Giacomo, Armin Karamzade, Marco Levorato, Carla Fabiana Chiasserini
2212.02379	Single image calibration using knowledge distillation approaches	Computer Vision and Pattern Recognition (cs.CV)	Khadidja Ould Amer, Oussama Hadjerci, Mohamed Abbas Hedjazi, Antoine Letienne
2212.02634	QFT: Post-training quantization via fast joint finetuning of all degrees of freedom	Machine Learning (stat.ML)	Alex Finkelstein, Ella Fuchs, Idan Tal, Mark Grobman, Niv Vosco, Eldad Meller
2212.02675	Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances	Computer Vision and Pattern Recognition (cs.CV)	Ajay Jaiswal, Tianlong Chen, Justin F. Rousseau, Yifan Peng, Ying Ding, Zhangyang Wang
2212.02687	Enabling and Accelerating Dynamic Vision Transformer Inference for Real-Time Applications	Computer Vision and Pattern Recognition (cs.CV)	Kavya Sreedhar, Jason Clemons, Rangharajan Venkatesan, Stephen W. Keckler, Mark Horowitz
2212.02770	CSQ: Growing Mixed-Precision Quantization Scheme with Bi-level Continuous Sparsification	Computer Vision and Pattern Recognition (cs.CV)	Lirui Xiao, Huanrui Yang, Zhen Dong, Kurt Keutzer, Li Du, Shanghang Zhang
2212.02781	QEBVerif: Quantization Error Bound Verification of Neural Networks	Machine Learning (cs.LG)	Yedi Zhang, Fu Song, Jun Sun
2212.02782	Self-Supervised Audio-Visual Speech Representations Learning By Multimodal Self-Distillation	Audio and Speech Processing (eess.AS)	Jing-Xuan Zhang, Genshun Wan, Zhen-Hua Ling, Jia Pan, Jianqing Gao, Cong Liu
2212.02800	Life-long Learning for Multilingual Neural Machine Translation with Knowledge Distillation	Computation and Language (cs.CL)	Yang Zhao, Junnan Zhu, Lu Xiang, Jiajun Zhang, Yu Zhou, Feifei Zhai, Chengqing Zong
2212.02931	Leveraging Different Learning Styles for Improved Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Usma Niyaz, Deepti R. Bathula
2212.03054	DisTRaC: Accelerating High Performance Compute Processing for Temporary Data Storage	Distributed, Parallel, and Cluster Computing (cs.DC)	Gabryel Mason-Williams, Dave Bond, Mark Basham
2212.03329	Enhancing Low-Density EEG-Based Brain-Computer Interfaces with Similarity-Keeping Knowledge Distillation	Machine Learning (cs.LG)	Xin-Yao Huang, Sung-Yu Chen, Chun-Shu Wei
2212.03415	Slimmable Pruned Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Hideaki Kuratsu, Atsuyoshi Nakamura
2212.03506	WIDER & CLOSER: Mixture of Short-channel Distillers for Zero-shot Cross-lingual Named Entity Recognition	Computation and Language (cs.CL)	Jun-Yu Ma, Beiduo Chen, Jia-Chen Gu, Zhen-Hua Ling, Wu Guo, Quan Liu, Zhigang Chen, Cong Liu
2212.03537	Efficient Stein Variational Inference for Reliable Distribution-lossless Network Pruning	Computer Vision and Pattern Recognition (cs.CV)	Yingchun Wang, Song Guo, Jingcai Guo, Weizhan Zhang, Yida Xu, Jie Zhang, Yi Liu
2212.03562	Accelerating Self-Imitation Learning from Demonstrations via Policy Constraints and Q-Ensemble	Machine Learning (cs.LG)	Chao Li
2212.03658	Learning Double-Compression Video Fingerprints Left from Social-Media Platforms	Computer Vision and Pattern Recognition (cs.CV)	Irene Amerini, Aris Anagnostopoulos, Luca Maiano, Lorenzo Ricciardi Celsi
2212.04486	DP-RAFT: A Differentially Private Recipe for Accelerated Fine-Tuning	Machine Learning (cs.LG)	Ashwinee Panda, Xinyu Tang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
2212.04500	Masked Video Distillation: Rethinking Masked Feature Modeling for Self-supervised Video Representation Learning	Computer Vision and Pattern Recognition (cs.CV)	Rui Wang, Dongdong Chen, Zuxuan Wu, Yinpeng Chen, Xiyang Dai, Mengchen Liu, Lu Yuan, Yu-Gang Jiang
2212.04569	Knowledge Distillation Applied to Optical Channel Equalization: Solving the Parallelization Problem of Recurrent Connection	Signal Processing (eess.SP)	Sasipim Srivallapanondh, Pedro J. Freire, Bernhard Spinnler, Nelson Costa, Antonio Napoli, Sergei K. Turitsyn, Jaroslaw E. Prilepsky
2212.04590	Learning Options via Compression	Machine Learning (cs.LG)	Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, Zico Kolter, Chelsea Finn
2212.04780	Genie: Show Me the Data for Quantization	Machine Learning (cs.LG)	Yongkweon Jeon, Chungman Lee, Ho-young Kim
2212.05031	Towards a learning-based performance modeling for accelerating Deep Neural Networks	Machine Learning (cs.LG)	Damiano Perri, Paolo Sylos Labini, Osvaldo Gervasi, Sergio Tasso, Flavio Vella
2212.05122	All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management	Machine Learning (cs.LG)	Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang
2212.05225	LEAD: Liberal Feature-based Distillation for Dense Retrieval	Information Retrieval (cs.IR)	Hao Sun, Xiao Liu, Yeyun Gong, Anlei Dong, Jian Jiao, Jingwen Lu, Yan Zhang, Daxin Jiang, Linjun Yang, Rangan Majumder, Nan Duan
2212.05250	Phases, Modalities, Temporal and Spatial Locality: Domain Specific ML Prefetcher for Accelerating Graph Analytics	Machine Learning (cs.LG)	Pengmiao Zhang, Rajgopal Kannan, Viktor K. Prasanna
2212.05271	GPU-accelerated Guided Source Separation for Meeting Transcription	Audio and Speech Processing (eess.AS)	Desh Raj, Daniel Povey, Sanjeev Khudanpur
2212.05330	Complete-to-Partial 4D Distillation for Self-Supervised Point Cloud Sequence Representation Learning	Computer Vision and Pattern Recognition (cs.CV)	Zhuoyang Zhang, Yuhao Dong, Yunze Liu, Li Yi
2212.05589	Learning Neural Volumetric Field for Point Cloud Geometry Compression	Computer Vision and Pattern Recognition (cs.CV)	Yueyu Hu, Yao Wang
2212.05603	Error-aware Quantization through Noise Tempering	Machine Learning (cs.LG)	Zheng Wang, Juncheng B Li, Shuhui Qu, Florian Metze, Emma Strubell
2212.05611	Accelerating Self-Supervised Learning via Efficient Training Strategies	Computer Vision and Pattern Recognition (cs.CV)	Mustafa Taha Koçyiğit, Timothy M. Hospedales, Hakan Bilen
2212.05698	MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations	Machine Learning (cs.LG)	Nicklas Hansen, Yixin Lin, Hao Su, Xiaolong Wang, Vikash Kumar, Aravind Rajeswaran
2212.05998	Continuation KD: Improved Knowledge Distillation through the Lens of Continuation Optimization	Machine Learning (cs.LG)	Aref Jafari, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart, Ali Ghodsi
2212.06144	Optimizing Learning Rate Schedules for Iterative Pruning of Deep Neural Networks	Machine Learning (cs.LG)	Shiyu Liu, Rohan Ghosh, John Tan Chong Min, Mehul Motani
2212.06145	AP: Selective Activation for De-sparsifying Pruned Neural Networks	Machine Learning (cs.LG)	Shiyu Liu, Rohan Ghosh, Dylan Tan, Mehul Motani
2212.06152	Accelerating Dataset Distillation via Model Augmentation	Machine Learning (cs.LG)	Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu
2212.07048	PD-Quant: Post-Training Quantization based on Prediction Difference Metric	Computer Vision and Pattern Recognition (cs.CV)	Jiawei Liu, Lin Niu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu
2212.07624	JAX-Accelerated Neuroevolution of Physics-informed Neural Networks: Benchmarks and Experimental Results	Neural and Evolutionary Computing (cs.NE)	Nicholas Sung Wei Yong, Jian Cheng Wong, Pao-Hsiung Chiu, Abhishek Gupta, Chinchun Ooi, Yew-Soon Ong
2212.07634	Gradient-based Intra-attention Pruning on Pre-trained Language Models	Computation and Language (cs.CL)	Ziqing Yang, Yiming Cui, Xin Yao, Shijin Wang
2212.08162	Huber-energy measure quantization	Machine Learning (stat.ML)	Gabriel Turinici
2212.08186	Learning Sparsity and Randomness for Data-driven Low Rank Approximation	Machine Learning (cs.LG)	Tiejin Chen, Yicheng Tao
2212.08254	RepQ-ViT: Scale Reparameterization for Post-Training Quantization of Vision Transformers	Computer Vision and Pattern Recognition (cs.CV)	Zhikai Li, Junrui Xiao, Lianwei Yang, Qingyi Gu
2212.08272	Communication-Efficient Federated Learning for Heterogeneous Edge Devices Based on Adaptive Gradient Quantization	Distributed, Parallel, and Cluster Computing (cs.DC)	Heting Liu, Fang He, Guohong Cao
2212.08349	Swing Distillation: A Privacy-Preserving Knowledge Distillation Framework	Machine Learning (cs.LG)	Junzhuo Li, Xinwei Wu, Weilong Dong, Shuangzhi Wu, Chao Bian, Deyi Xiong
2212.08379	GeneFormer: Learned Gene Compression using Transformer-based Context Modeling	Machine Learning (cs.LG)	Zhanbei Cui, Yu Liao, Tongda Xu, Yan Wang
2212.08476	SteerNeRF: Accelerating NeRF Rendering via Smooth Viewpoint Trajectory	Computer Vision and Pattern Recognition (cs.CV)	Sicheng Li, Hao Li, Yue Wang, Yiyi Liao, Lu Yu
2212.08663	Randomized Quantization for Data Agnostic Representation Learning	Computer Vision and Pattern Recognition (cs.CV)	Huimin Wu, Chenyang Lei, Xiao Sun, Peng-Shuai Wang, Qifeng Chen, Kwang-Ting Cheng, Stephen Lin, Zhirong Wu
2212.08974	3D Point Cloud Pre-training with Knowledge Distillation from 2D Images	Computer Vision and Pattern Recognition (cs.CV)	Yuan Yao, Yuanhan Zhang, Zhenfei Yin, Jiebo Luo, Wanli Ouyang, Xiaoshui Huang
2212.09019	Fast FullSubNet: Accelerate Full-band and Sub-band Fusion Model for Single-channel Speech Enhancement	Audio and Speech Processing (eess.AS)	Xiang Hao, Xiaofei Li
2212.09246	I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation	Computation and Language (cs.CL)	Chandra Bhagavatula, Jena D. Hwang, Doug Downey, Ronan Le Bras, Ximing Lu, Keisuke Sakaguchi, Swabha Swayamdipta, Peter West, Yejin Choi
2212.09335	Distilling Vision-Language Pre-training to Collaborate with Weakly-Supervised Temporal Action Localization	Computer Vision and Pattern Recognition (cs.CV)	Chen Ju, Kunhao Zheng, Jinxiang Liu, Peisen Zhao, Ya Zhang, Jianlong Chang, Yanfeng Wang, Qi Tian
2212.09409	Multi-View Knowledge Distillation from Crowd Annotations for Out-of-Domain Generalization	Computation and Language (cs.CL)	Dustin Wright, Isabelle Augenstein
2212.09458	Exploring Optimal Substructure for Out-of-distribution Generalization via Feature-targeted Model Pruning	Machine Learning (cs.LG)	Yingchun Wang, Jingcai Guo, Song Guo, Weizhan Zhang, Jie Zhang
2212.09483	Adaptive Control of Client Selection and Gradient Compression for Efficient Federated Learning	Distributed, Parallel, and Cluster Computing (cs.DC)	Zhida Jiang, Yang Xu, Hongli Xu, Zhiyuan Wang, Chen Qian
2212.09721	KNIFE: Knowledge Distillation with Free-Text Rationales	Computation and Language (cs.CL)	Aaron Chan, Zhiyuan Zeng, Wyatt Lake, Brihi Joshi, Hanjie Chen, Xiang Ren
2212.09735	Correspondence Distillation from NeRF-based GAN	Computer Vision and Pattern Recognition (cs.CV)	Yushi Lan, Chen Change Loy, Bo Dai
2212.09811	Memory-efficient NLLB-200: Language-specific Expert Pruning of a Massively Multilingual Machine Translation Model	Computation and Language (cs.CL)	Yeskendir Koishekenov, Vassilina Nikoulina, Alexandre Berard
2212.09948	MM-3DScene: 3D Scene Understanding by Customizing Masked Modeling with Informative-Preserved Reconstruction and Self-Distilled Consistency	Computer Vision and Pattern Recognition (cs.CV)	Mingye Xu, Mutian Xu, Tong He, Wanli Ouyang, Yali Wang, Xiaoguang Han, Yu Qiao
2212.10005	Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning	Machine Learning (cs.LG)	Ramya Hebbalaguppe, Rishabh Patra, Tirtharaj Dash, Gautam Shroff, Lovekesh Vig
2212.10192	Adam: Dense Retrieval Distillation with Adaptive Dark Examples	Computation and Language (cs.CL)	Chang Liu, Chongyang Tao, Xiubo Geng, Tao Shen, Dongyan Zhao, Can Xu, Binxing Jiao, Daxin Jiang
2212.10200	Redistribution of Weights and Activations for AdderNet Quantization	Computer Vision and Pattern Recognition (cs.CV)	Ying Nie, Kai Han, Haikang Diao, Chuanjian Liu, Enhua Wu, Yunhe Wang
2212.10220	CSMPQ:Class Separability Based Mixed-Precision Quantization	Computer Vision and Pattern Recognition (cs.CV)	Mingkai Wang, Taisong Jin, Miaohui Zhang, Zhengtao Yu
2212.10252	MDL-based Compressing Sequential Rules	Artificial Intelligence (cs.AI)	Xinhong Chen, Wensheng Gan, Shicheng Wan, Tianlong Gu
2212.10423	Fine-Grained Distillation for Long Document Retrieval	Information Retrieval (cs.IR)	Yucheng Zhou, Tao Shen, Xiubo Geng, Chongyang Tao, Guodong Long, Can Xu, Daxin Jiang
2212.10465	SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization	Computation and Language (cs.CL)	Hyunwoo Kim, Jack Hessel, Liwei Jiang, Ximing Lu, Youngjae Yu, Pei Zhou, Ronan Le Bras, Malihe Alikhani, Gunhee Kim, Maarten Sap, Yejin Choi
2212.10534	DISCO: Distilling Phrasal Counterfactuals with Large Language Models	Computation and Language (cs.CL)	Zeming Chen, Qiyue Gao, Kyle Richardson, Antoine Bosselut, Ashish Sabharwal
2212.10670	In-context Learning Distillation: Transferring Few-shot Learning Ability of Pre-trained Language Models	Computation and Language (cs.CL)	Yukun Huang, Yanda Chen, Zhou Yu, Kathleen McKeown
2212.10719	AEStream: Accelerated event-based processing with coroutines	Distributed, Parallel, and Cluster Computing (cs.DC)	Jens Egholm Pedersen, Jörg Conradt
2212.10878	Automatic Network Adaptation for Ultra-Low Uniform-Precision Quantization	Computer Vision and Pattern Recognition (cs.CV)	Seongmin Park, Beomseok Kwon, Jieun Lim, Kyuyoung Sim, Tae-Ho Kim, Jungwook Choi
2212.10950	Incremental Learning for Neural Radiance Field with Uncertainty-Filtered Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Mengqi Guo, Chen Li, Gim Hee Lee
2212.11091	Exploring Content Relationships for Distilling Efficient GANs	Computer Vision and Pattern Recognition (cs.CV)	Lizhou You, Mingbao Lin, Tie Hu, Fei Chao, Rongrong Ji
2212.11353	Contrastive Distillation Is a Sample-Efficient Self-Supervised Loss Policy for Transfer Learning	Computation and Language (cs.CL)	Chris Lengerich, Gabriel Synnaeve, Amy Zhang, Hugh Leather, Kurt Shuster, François Charton, Charysse Redwood
2212.11506	Accelerating Barnes-Hut t-SNE Algorithm by Efficient Parallelization on Multi-Core CPUs	Machine Learning (cs.LG)	Narendra Chaudhary, Alexander Pivovar, Pavel Yakovlev, Andrey Gorshkov, Sanchit Misra
2212.11574	Accelerating CNN inference on long vector architectures via co-design	Distributed, Parallel, and Cluster Computing (cs.DC)	Sonia Rani Gupta, Nikela Papadopoulou, Miquel Pericas
2212.12213	Finetuning for Sarcasm Detection with a Pruned Dataset	Computation and Language (cs.CL)	Ishita Goyal, Priyank Bhandia, Sanjana Dulam
2212.12631	A Labelled Sample Compression Scheme of Size at Most Quadratic in the VC Dimension	Machine Learning (cs.LG)	Farnam Mansouri, Sandra Zilles
2212.12649	Hyperspherical Loss-Aware Ternary Quantization	Computer Vision and Pattern Recognition (cs.CV)	Dan Liu, Xue Liu
2212.12651	Pruning On-the-Fly: A Recoverable Pruning Method without Fine-tuning	Computer Vision and Pattern Recognition (cs.CV)	Dan Liu, Xue Liu
2212.12653	Hyperspherical Quantization: Toward Smaller and More Accurate Models	Computer Vision and Pattern Recognition (cs.CV)	Dan Liu, Xi Chen, Chen Ma, Xue Liu
2212.12738	T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation	Machine Learning (cs.LG)	Cuiying Huo, Di Jin, Yawen Li, Dongxiao He, Yu-Bin Yang, Lingfei Wu
2212.12770	COLT: Cyclic Overlapping Lottery Tickets for Faster Pruning of Convolutional Neural Networks	Computer Vision and Pattern Recognition (cs.CV)	Md. Ismail Hossain, Mohammed Rakib, M. M. Lutfe Elahi, Nabeel Mohammed, Shafin Rahman
2212.12965	BD-KD: Balancing the Divergences for Online Knowledge Distillation	Computer Vision and Pattern Recognition (cs.CV)	Ibtihel Amara, Nazanin Sepahvand, Brett H. Meyer, Warren J. Gross, James J. Clark
2212.13180	Prototype-guided Cross-task Knowledge Distillation for Large-scale Models	Computer Vision and Pattern Recognition (cs.CV)	Deng Li, Aming Wu, Yahong Han, Qi Tian
2212.13392	DeepCuts: Single-Shot Interpretability based Pruning for BERT	Computation and Language (cs.CL)	Jasdeep Singh Grover, Bhavesh Gawri, Ruskin Raj Manku
2212.13659	Latent Discretization for Continuous-time Sequence Compression	Machine Learning (cs.LG)	Ricky T. Q. Chen, Matthew Le, Matthew Muckley, Maximilian Nickel, Karen Ullrich
2212.13766	OVO: One-shot Vision Transformer Search with Online distillation	Computer Vision and Pattern Recognition (cs.CV)	Zimian Wei, Hengyue Pan, Xin Niu, Dongsheng Li
2212.13893	Machine learning for accelerating the discovery of high performance low-cost solar cells: a systematic review	Signal Processing (eess.SP)	Satyam Bhatti, Habib Ullah Manzoor, Bruno Michel, Ruy Sebastian Bonilla, Richard Abrams, Ahmed Zoha, Sajjad Hussain, Rami Ghannam
2212.13919	Siamese Sleep Transformer For Robust Sleep Stage Scoring With Self-knowledge Distillation and Selective Batch Sampling	Signal Processing (eess.SP)	Heon-Gyu Kwak, Young-Seok Kweon, Gi-Hwan Shin
2212.14169	Discriminator-Cooperated Feature Map Distillation for GAN Compression	Computer Vision and Pattern Recognition (cs.CV)	Tie Hu, Mingbao Lin, Lizhou You, Fei Chao, Rongrong Ji
2212.14306	Zero-Shot Object Segmentation through Concept Distillation from Generative Image Foundation Models	Computer Vision and Pattern Recognition (cs.CV)	Mischa Dombrowski, Hadrien Reynaud, Matthew Baugh, Bernhard Kainz
2212.14760	Deep Hierarchy Quantization Compression algorithm based on Dynamic Sampling	Machine Learning (cs.LG)	Wan Jiang, Gang Liu, Xiaofeng Chen, Yipeng Zhou