Folders and files
| Name | Name | Last commit date | ||
|---|---|---|---|---|
Learning with Feature-Dependent Label Noise: A Progressive Approach (ICLR 2021, spotlight) Paper
- PyTorch 1.6 (Other versions >= 1.0 should also work)
- Python 3.8.5 (Other Python 3.x should also work)
- tqdm, termcolor, etc (which can be easily installed via pip)
- The folder cifar contains the code for generating PMD noise and running on synthetic datasets.
- The folder clothing1m contains the code for running on Clothing1M dataset.
- The folder Food101 contains the code for running on Food-101N dataset.
@inproceedings{prog_noise_iclr2021,
title={Learning with Feature-Dependent Label Noise: A Progressive Approach},
author={Zhang, Yikai and Zheng, Songzhu and Wu, Pengxiang and Goswami, Mayank and Chen, Chao},
booktitle={ICLR},
year={2021}
}