fair machine learning

Fair Domain Generalization with Heterogeneous Sensitive Attributes Across Domains WACV 2025 FairTP: A Prolonged Fairness Framework for Traffic Prediction AAAI 2025 Learning Causally Disentangled Representations for Fair Personality Detection IJCAI 2025 Towards Fairness with Limited Demographics via Disentangled Learning IJCAI 2025 Aequitas Flow: Streamlining Fair ML Experimentation JMLR 2024 Data-Centric Explainable Debiasing for Improving Fairness in Pre-trained Language Models ACL 2024 Demystifying Algorithmic Fairness in an Uncertain World AAAI 2024 Fair Graph Learning Using Constraint-Aware Priority Adjustment and Graph Masking in River Networks AAAI 2024 Fairness-Aware Meta-Learning via Nash Bargaining NeurIPS 2024 FairWASP: Fast and Optimal Fair Wasserstein Pre-processing AAAI 2024 Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach ICLR 2024 Long-Term Fair Decision Making through Deep Generative Models AAAI 2024 Mind the Gap: A Causal Perspective on Bias Amplification in Prediction & Decision-Making NeurIPS 2024 Mitigating Bias for Question Answering Models by Tracking Bias Influence NAACL 2024 On Socially Fair Low-Rank Approximation and Column Subset Selection NeurIPS 2024 Structural Fairness-aware Active Learning for Graph Neural Networks ICLR 2024 To Pool or Not To Pool: Analyzing the Regularizing Effects of Group-Fair Training on Shared Models AISTATS 2024 Debiased Automatic Speech Recognition for Dysarthric Speech via Sample Reweighting with Sample Affinity Test Interspeech 2023 Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy Learning ICML 2023 Fairness in Streaming Submodular Maximization over a Matroid Constraint ICML 2023 Learning Antidote Data to Individual Unfairness ICML 2023 Provable Detection of Propagating Sampling Bias in Prediction Models AAAI 2023 Revisiting Fair-PAC Learning and the Axioms of Cardinal Welfare AISTATS 2023 The Measure and Mismeasure of Fairness JMLR 2023 Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes ICML 2023