Curriculum by Smoothing (NeurIPS 2020)
The official PyTorch implementation of Curriculum by Smoothing (NeurIPS 2020, Spotlight).
For any questions regarding the codebase, please send a message at: [email protected]
USAGE: Simply use the code by running:
python3 main.py --dataset
For example, to train a ResNet on CIFAR10 and the data is saved in ./data/
, we can run:
python3 main.py --dataset cifar10 --alg res --data ./data/
For new expeiments it is important to tune the following hyperparameters:
--std --std_factor --epoch
LINK: https://arxiv.org/abs/2003.01367
This codebase has experiments for image classification and transfer learning.
If you use this codebase or find this repository helpful then please cite our paper:
@article{sinha2020curriculum,
title={Curriculum By Smoothing},
author={Sinha, Samarth and Garg, Animesh and Larochelle, Hugo},
journal={Advances in Neural Information Processing Systems},
volume={33},
year={2020}
}