/DeepAUC

Stochastic AUC Maximization with Deep Neural Networks

Primary LanguagePython

Deep AUC Maximization pdf

This is the official implementation of the paper "Stochastic AUC Maximization with Deep Neural Networks" published on ICLR2020.

Installation

Python=3.5
Numpy=1.18.5 
Scipy=1.2.1
Scikit-Learn=0.20.3
Pillow=5.0.0
Tensorflow>=1.10.0

Run

python PPD_SG.py/PPD_AdaGrad.py --dataset=10 --train_batch_size=128 --use_L2=False --split_index=4 --lr=0.01 --keep_index=0.1 --t0=200

Hyperparameter tuning

gamma=[500, 1000, 2000, ...]
eta = [0.1, 0.01, ...]
T0=[1000, 2000, 3000, ...,]

Bibtex

If you use this repository in your work, please cite our paper:

@inproceedings{
Liu2020Stochastic,
title={Stochastic AUC Maximization with Deep Neural Networks},
author={Mingrui Liu and Zhuoning Yuan and Yiming Ying and Tianbao Yang},
booktitle={International Conference on Learning Representations},
year={2020},
url={https://openreview.net/forum?id=HJepXaVYDr}
}