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stat.ML2026
Beyond Procedure: Substantive Fairness in Conformal Prediction
Pengqi Liu, Zijun Yu, Mouloud Belbahri +3
Conformal prediction (CP) offers distribution-free uncertainty quantification for machine learning models, yet its interplay with fairness in downstream decision-making remains und…
stat.ML2026
Federated Measurement of Demographic Disparities from Quantile Sketches
Arthur Charpentier, Agathe Fernandes Machado, Olivier Côté +1
Many fairness goals are defined at a population level that misaligns with siloed data collection, which remains unsharable due to privacy regulations. Horizontal federated learning…
stat.ML2025
Decomposing Direct and Indirect Biases in Linear Models under Demographic Parity Constraint
Bertille Tierny, Arthur Charpentier, François Hu
Linear models are widely used in high-stakes decision-making due to their simplicity and interpretability. Yet when fairness constraints such as demographic parity are introduced,…