Understanding Fairness Surrogate Functions in Algorithmic Fairness

Accepted by TMLR 2024

Openreview Link: https://openreview.net/forum?id=iBgmoMTlaz

Files

The experiments are in ./fairness/, while the tools are in ./lib/.

Start

Run ./fairness/Adult/ex1.py. Please change the path of the datasets in prepare_adult_data.py. The guildeline is the same for Bank and COMPAS.

Citation

@article{yao2024understanding,
  title={Understanding Fairness Surrogate Functions in Algorithmic Fairness},
  author={Yao, Wei and Zhou, Zhanke and Li, Zhicong and Han, bo and Liu, Yong},
  journal={Transactions on Machine Learning Research},
  year={2024}
}

Acknowledgement

Our codes are modified from Fairness Constraints: Mechanisms for Fair Classification.