Obtaining Fairness using Optimal Transport Theory
Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2357-2365, 2019.
In the fair classification setup, we recast the links between fairness and predictability in terms of probability metrics. We analyze repair methods based on mapping conditional distributions to the Wasserstein barycenter. We propose a Random Repair which yields a tradeoff between minimal information loss and a certain amount of fairness.