sensitive attribute

A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges IJCAI 2023 Bias Propagation in Federated Learning ICLR 2023 Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors NeurIPS 2023 FairLISA: Fair User Modeling with Limited Sensitive Attributes Information NeurIPS 2023 Fairness-aware Contrastive Learning with Partially Annotated Sensitive Attributes ICLR 2023 Fair Representation Learning for Recommendation: A Mutual Information Perspective AAAI 2023 Fair Representation Learning with Unreliable Labels AISTATS 2023 Human-Guided Fair Classification for Natural Language Processing ICLR 2023 Invariant Representations with Stochastically Quantized Neural Networks AAAI 2023 MMD-B-Fair: Learning Fair Representations with Statistical Testing AISTATS 2023 Shielded Representations: Protecting Sensitive Attributes Through Iterative Gradient-Based Projection ACL 2023 Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes ICML 2023 Controlling Bias Exposure for Fair Interpretable Predictions EMNLP 2022 Counterfactual Fairness with Partially Known Causal Graph NeurIPS 2022 Does Representational Fairness Imply Empirical Fairness? AACL 2022 EqGNN: Equalized Node Opportunity in Graphs AAAI 2022 Fairness without the Sensitive Attribute via Causal Variational Autoencoder IJCAI 2022 Generalized Demographic Parity for Group Fairness ICLR 2022 Addressing fairness in classification with a model-agnostic multi-objective algorithm UAI 2021 Detect and Perturb: Neutral Rewriting of Biased and Sensitive Text via Gradient-based Decoding EMNLP 2021 Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach AAAI 2021 Fairness-aware News Recommendation with Decomposed Adversarial Learning AAAI 2021 Fair Representations by Compression AAAI 2021 Achieving Equalized Odds by Resampling Sensitive Attributes NeurIPS 2020 A General Approach to Fairness with Optimal Transport AAAI 2020