Fair regression with demographic parity penalty is recast as optimal transport, yielding optimal maps under Wasserstein-2 and total variation penalties that work in both aware and unaware regimes.
Equality as a moral ideal.Ethics, 98(1):21–43, October 1987
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The Pareto frontier of fair algorithmic decisions consists of deterministic group-specific threshold rules on predicted success probabilities, which can include upper bounds for some fairness metrics and holds independently of model training approach.
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Geometry of Relaxed Fair Regression: A Unified Framework for Aware and Unaware Settings
Fair regression with demographic parity penalty is recast as optimal transport, yielding optimal maps under Wasserstein-2 and total variation penalties that work in both aware and unaware regimes.
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Fairness vs Performance: Characterizing the Pareto Frontier of Algorithmic Decision Systems
The Pareto frontier of fair algorithmic decisions consists of deterministic group-specific threshold rules on predicted success probabilities, which can include upper bounds for some fairness metrics and holds independently of model training approach.