Obtaining Fairness using Optimal Transport Theory

作者: Paula Gordaliza, Eustasio del Barrio, Gamboa Fabrice, Jean-Michel Loubes

摘要

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.

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