Authors of FedML (https://fedml.ai) have 7 papers that got accepted to NeurIPS 2020. Big congratulations!!! Here is the publication list. Highlighted ones are related to large-scale distributed learning and federated learning. Can the other papers get marriage with FedML? Let's stay tuned 🙂
***[1] J. So, B. Guler, and A.S. Avestimehr, "A Scalable Approach for Privacy-Preserving Collaborative Machine Learning"
[2] M. Kalan, Z. Fabian, A.S. Avestimehr, and M. Soltanolkotabi, "Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural Networks"
***[3] C. He, M. Annavaram, and A.S. Avestimehr, "Group Knowledge Transfer: Collaborative Training of Large CNNs on the Edge"
[4] Mi Zhang. Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?
***[5] Hongyi Wang. Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
[6] Peilin Zhao. Adversarial Sparse Transformer for Time Series Forecasting
[7] Peilin Zhao. RetroXpert: Decompose Retrosynthesis Prediction like A Chemist