• Corpus ID: 220683906

# Minimax Pareto Fairness: A Multi Objective Perspective

@article{Martnez2020MinimaxPF,
title={Minimax Pareto Fairness: A Multi Objective Perspective},
author={Natalia Mart{\'i}nez and Mart{\'i}n Bertr{\'a}n and Guillermo Sapiro},
journal={Proceedings of machine learning research},
year={2020},
volume={119},
pages={
6755-6764
}
}
• Published 1 July 2020
• Computer Science
• Proceedings of machine learning research
In this work we formulate and formally characterize group fairness as a multi-objective optimization problem, where each sensitive group risk is a separate objective. We propose a fairness criterion where a classifier achieves minimax risk and is Pareto-efficient w.r.t. all groups, avoiding unnecessary harm, and can lead to the best zero-gap model if policy dictates so. We provide a simple optimization algorithm compatible with deep neural networks to satisfy these constraints. Since our method…
74 Citations

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