fair classification

Pairwise Fairness for Ordinal Regression AISTATS 2022 Prototype Based Classification from Hierarchy to Fairness ICML 2022 VACA: Designing Variational Graph Autoencoders for Causal Queries AAAI 2022 Adaptive Sampling for Minimax Fair Classification NeurIPS 2021 Addressing fairness in classification with a model-agnostic multi-objective algorithm UAI 2021 An Information-theoretic Approach to Distribution Shifts NeurIPS 2021 A Novel Estimator of Mutual Information for Learning to Disentangle Textual Representations ACL 2021 Bias-tolerant Fair Classification ACML 2021 Classification with abstention but without disparities UAI 2021 Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder AAAI 2021 Fair Classification with Adversarial Perturbations NeurIPS 2021 Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees ICML 2021 Mitigating Bias in Session-based Cyberbullying Detection: A Non-Compromising Approach ACL 2021 Optimized Score Transformation for Consistent Fair Classification JMLR 2021 The Effect of Round-Trip Translation on Fairness in Sentiment Analysis EMNLP 2021 Differentially Private and Fair Classification via Calibrated Functional Mechanism AAAI 2020 Fair Multiple Decision Making Through Soft Interventions NeurIPS 2020 Fairness with Overlapping Groups; a Probabilistic Perspective NeurIPS 2020 Identifying and Correcting Label Bias in Machine Learning AISTATS 2020 Probably Approximately Correct Constrained Learning NeurIPS 2020 Rényi Fair Inference ICLR 2020 Towards Threshold Invariant Fair Classification UAI 2020 Average Individual Fairness: Algorithms, Generalization and Experiments NeurIPS 2019 Fairness Constraints: A Flexible Approach for Fair Classification JMLR 2019 Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification NeurIPS 2019