fair representation

Learning Fair Representations with Kolmogorov-Arnold Networks AAAI 2026 Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning AISTATS 2024 FADES: Fair Disentanglement with Sensitive Relevance CVPR 2024 Learning Fair Representations for Recommendation via Information Bottleneck Principle IJCAI 2024 Counterfactually Fair Representation NeurIPS 2023 Efficient fair PCA for fair representation learning AISTATS 2023 Fair Data Representation for Machine Learning at the Pareto Frontier JMLR 2023 Fair Representation Learning for Recommendation: A Mutual Information Perspective AAAI 2023 Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint NeurIPS 2023 Invariant Representations with Stochastically Quantized Neural Networks AAAI 2023 MMD-B-Fair: Learning Fair Representations with Statistical Testing AISTATS 2023 Representation with Incomplete Votes AAAI 2023 Conditional Supervised Contrastive Learning for Fair Text Classification EMNLP 2022 Fair Normalizing Flows ICLR 2022 Learning fair representation with a parametric integral probability metric ICML 2022 Adversarial Scrubbing of Demographic Information for Text Classification EMNLP 2021 Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation AAAI 2021 Fair Representations by Compression AAAI 2021 Learning Smooth and Fair Representations AISTATS 2021 Mitigating Face Recognition Bias via Group Adaptive Classifier CVPR 2021 Conditional Learning of Fair Representations ICLR 2020 Learning Fair Representations for Kernel Models AISTATS 2020 Neutralizing Self-Selection Bias in Sampling for Sortition NeurIPS 2020 Discovering Fair Representations in the Data Domain CVPR 2019 Fair Algorithms for Clustering NeurIPS 2019