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.
A minimax framework for quantifying risk-fairness trade-off in regression.The Annals of Statistics, 50(4):2416–2442, August 2022
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Derives closed-form optimal counterfactually fair regressor via barycentric quantile map and proves Õ(n^{-1/3}) finite-sample fairness and risk bounds for discretized post-processing under mild assumptions.
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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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Counterfactually Fair Regression via Optimal Transport
Derives closed-form optimal counterfactually fair regressor via barycentric quantile map and proves Õ(n^{-1/3}) finite-sample fairness and risk bounds for discretized post-processing under mild assumptions.