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V. Chen

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Jul 2026

End-to-End Fairness Optimization with Fair Decision-Focused Learning

End-to-end fairness optimization (E2EFO) is introduced as a unifying framework that integrates fairness across the prediction-to-decision pipeline and fair decision-focused learning (FDFL), a training paradigm that jointly accounts for prediction accuracy, prediction fairness, and decision regret.

Yu Wang, V. Chen · 0 citations

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