Awesome
learning-to-reweight-examples
Code for paper Learning to Reweight Examples for Robust Deep Learning. [arxiv]
Environment
We tested the code on
- tensorflow 1.10
- python 3
Other dependencies:
- numpy
- tqdm
- six
- protobuf
Installation
The following command makes the protobuf configurations.
make
MNIST binary classification experiment
python -m mnist.mnist_train --exp ours
Please see mnist/mnist_train.py
for more options.
CIFAR noisy label experiments
Download CIFAR dataset
bash cifar/download_cifar.sh ./data
Config files are located in cifar/configs
. For ResNet-32, use
cifar/configs/cifar-resnet-32.prototxt
. For Wide ResNet-28, use
cifar/configs/cifar-wide-resnet-28-10.prototxt
.
CIFAR-10/100 uniform flip noise experiment
python -m cifar.cifar_train --config [CONFIG]
Please see cifar/cifar_train.py
for more options.
CIFAR-10/100 background flip noise experiment
python -m cifar.cifar_train_background --config [CONFIG]
Please see cifar/cifar_train_background.py
for more options.
Citation
If you use our code, please consider cite the following: Mengye Ren, Wenyuan Zeng, Bin Yang, Raquel Urtasun. Learning to Reweight Examples for Robust Deep Learning. ICML 2018.
@inproceedings{ren18l2rw,
author = {Mengye Ren and Wenyuan Zeng and Bin Yang and Raquel Urtasun},
title = {Learning to Reweight Examples for Robust Deep Learning},
booktitle = {ICML},
year = {2018},
}