Boosting Co-teaching with Compression Regularization for Label Noise
Nested-Co-teaching
([email protected]) Pytorch implementation of paper “Boosting Co-teaching with Compression Regularization for Label Noise”
If our project is helpful for your research, please consider citing :
@inproceedings{chen2021boosting,
title={Boosting Co-teaching with Compression Regularization for Label Noise},
author={Chen, Yingyi and Shen, Xi and Hu, Shell Xu and Suykens, Johan AK},
booktitle={CVPR Learning from Limited and Imperfect Data (L2ID) workshop},
year={2021}
}
Our model can be learnt in a single GPU GeForce GTX 1080Ti (12G), this code has been tested with Pytorch 1.7.1
1. Toy Results
The nested regularization allows us to learn ordered representation which would be useful to combat noisy label. In this toy example, we aim at learning a projection from X to Y with noisy pairs. By adding nested