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This repo contains the codes for our work “Restricted orthogonal gradient projection for continual learning”.

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ROGO

This repo contains the codes for our work “Restricted orthogonal gradient projection for continual learning”.

Data Preparation

The dataset for PMNIST, CIFAR-100, and Mixture will be automatically downloaded. For the experiments on MiniImageNet, please download the train_data and test_data, and place them under the data folder.

Experiments

This repository currently contains experiments reported in the paper for Permuted MNIST, 10-split CIFAR-100, 20-split MiniImageNet and the Mixture datasets. All these experiments can be run using the following command:

bash run.sh

Citation

@article{YANG202398,
title = {Restricted orthogonal gradient projection for continual learning},
journal = {AI Open},
volume = {4},
pages = {98-110},
year = {2023},
issn = {2666-6510},
doi = {https://doi.org/10.1016/j.aiopen.2023.08.010},
url = {https://www.sciencedirect.com/science/article/pii/S2666651023000128},
author = {Zeyuan Yang and Zonghan Yang and Yichen Liu and Peng Li and Yang Liu},
}

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This repo contains the codes for our work “Restricted orthogonal gradient projection for continual learning”.

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