group fairness

Approximate Group Fairness for Clustering ICML 2021 Best-case lower bounds in online learning NeurIPS 2021 Blind Pareto Fairness and Subgroup Robustness ICML 2021 Controlling Fairness and Bias in Dynamic Learning-to-Rank (Extended Abstract) IJCAI 2021 Evaluating model performance under worst-case subpopulations NeurIPS 2021 Fair Clustering Under a Bounded Cost NeurIPS 2021 Fair Exploration via Axiomatic Bargaining NeurIPS 2021 Fair for All: Best-effort Fairness Guarantees for Classification AISTATS 2021 Fair Mixup: Fairness via Interpolation ICLR 2021 Fairness for Image Generation with Uncertain Sensitive Attributes ICML 2021 Fair Voice Biometrics: Impact of Demographic Imbalance on Group Fairness in Speaker Recognition Interspeech 2021 Group Fairness by Probabilistic Modeling with Latent Fair Decisions AAAI 2021 Learning Optimal Predictive Checklists NeurIPS 2021 Matchings with Group Fairness Constraints: Online and Offline Algorithms IJCAI 2021 On the Problem of Underranking in Group-Fair Ranking ICML 2021 Testing Group Fairness via Optimal Transport Projections ICML 2021 To be Robust or to be Fair: Towards Fairness in Adversarial Training ICML 2021 Towards Reducing Biases in Combining Multiple Experts Online IJCAI 2021 Training Over-parameterized Models with Non-decomposable Objectives NeurIPS 2021 Achieving Equalized Odds by Resampling Sensitive Attributes NeurIPS 2020 A Fair Classifier Using Kernel Density Estimation NeurIPS 2020 Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference NeurIPS 2020 Equalized odds postprocessing under imperfect group information AISTATS 2020 FACT: A Diagnostic for Group Fairness Trade-offs ICML 2020 Fairness for Robust Log Loss Classification AAAI 2020