fair representation learning

Causality-Inspired Disentanglement for Fair Graph Neural Networks IJCAI 2025 Rethinking Fair Representation Learning for Performance-Sensitive Tasks ICLR 2025 Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning AISTATS 2024 FADES: Fair Disentanglement with Sensitive Relevance CVPR 2024 Fair Representation Learning with Maximum Mean Discrepancy Distance Constraint (Student Abstract) AAAI 2024 Towards Poisoning Fair Representations ICLR 2024 Utility-Fairness Trade-Offs and How to Find Them CVPR 2024 Fair Representation Learning for Recommendation: A Mutual Information Perspective AAAI 2023 Fair Representation Learning with Unreliable Labels AISTATS 2023 FARE: Provably Fair Representation Learning with Practical Certificates ICML 2023 Invariant Representations with Stochastically Quantized Neural Networks AAAI 2023 MMD-B-Fair: Learning Fair Representations with Statistical Testing AISTATS 2023 Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness ICML 2022 Fair Contrastive Learning for Facial Attribute Classification CVPR 2022 Fair Representation Learning through Implicit Path Alignment ICML 2022 Self-Supervised Fair Representation Learning without Demographics NeurIPS 2022 SoFaiR: Single Shot Fair Representation Learning IJCAI 2022 Representation Learning With Statistical Independence to Mitigate Bias WACV 2021 Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning NeurIPS 2020 Inherent Tradeoffs in Learning Fair Representations NeurIPS 2019 Learning Controllable Fair Representations AISTATS 2019