Active Sampling for Min-Max Fairness

This repository contains code for our ICML 2022 paper Active Sampling for Min-Max Fairness.

In order to reproduce the experiments of our paper, do the following:

1. install all required packages as specified in environment.yml

2. run one of the scripts experiment_drug_consumption_dataset.py, experiment_drug_consumption_dataset_tradeoff_curve.py, experiment_COMPAS_dataset.py, or experiment_diabetes_dataset.py (when running a script, the required dataset will be downloaded automatically --- make sure you are connected to the internet)

Citation

If you publish material that uses this code, please cite our paper:

@inproceedings{abernethy2022ActiveSampling,
title={Active Sampling for Min-Max Fairness},
author={Abernethy, Jacob and Awasthi, Pranjal and Kleindessner, Matthäus and Morgenstern, Jamie and Russell, Chris and Zhang, Jie},
year={2022},
booktitle={International Conference on Machine Learning (ICML)}
}

Security

See CONTRIBUTING for more information.

License

This project is licensed under the Apache-2.0 License.