fair classification

Bayes-Optimal Fair Classification with Linear Disparity Constraints via Pre-, In-, and Post-processing JMLR 2026 Bayes-Optimal Fair Classification with Multiple Sensitive Features AAAI 2026 Demographic Parity in Regression and Classification Within the Unawareness Framework JMLR 2026 OxEnsemble: Fair Ensembles for Low-Data Classification MIDL 2026 FROC: Building Fair ROC from a Trained Classifier AAAI 2025 Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification AAAI 2024 Empirical Likelihood for Fair Classification ICLR 2024 Fair Active Learning in Low-Data Regimes UAI 2024 Post-hoc bias scoring is optimal for fair classification ICLR 2024 Quality-Diversity Generative Sampling for Learning with Synthetic Data AAAI 2024 Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization AISTATS 2024 Adapting Fairness Interventions to Missing Values NeurIPS 2023 Fair and Optimal Classification via Post-Processing ICML 2023 FaiREE: fair classification with finite-sample and distribution-free guarantee ICLR 2023 Fair learning with Wasserstein barycenters for non-decomposable performance measures AISTATS 2023 Faster Fair Machine via Transferring Fairness Constraints to Virtual Samples AAAI 2023 FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data ICLR 2023 Human-Guided Fair Classification for Natural Language Processing ICLR 2023 Individually Fair Learning with One-Sided Feedback ICML 2023 Minimax AUC Fairness: Efficient Algorithm with Provable Convergence AAAI 2023 EqGNN: Equalized Node Opportunity in Graphs AAAI 2022 Fair Classification with Instance-dependent Label Noise CLeaR 2022 Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values AAAI 2022 Group-Aware Threshold Adaptation for Fair Classification AAAI 2022 Learning Disentangled Textual Representations via Statistical Measures of Similarity ACL 2022