statistical parity

Post-processing for Fair Regression via Explainable SVD AISTATS 2025 The Disparate Benefits of Deep Ensembles ICML 2025 Differentially Private Post-Processing for Fair Regression ICML 2024 Reconciling Predictive and Statistical Parity: A Causal Approach AAAI 2024 Revisiting Fair-PAC Learning and the Axioms of Cardinal Welfare AISTATS 2023 Scalable Spectral Clustering with Group Fairness Constraints AISTATS 2023 EqGNN: Equalized Node Opportunity in Graphs AAAI 2022 Fair Wrapping for Black-box Predictions NeurIPS 2022 Inherent Tradeoffs in Learning Fair Representations JMLR 2022 On Coresets for Fair Regression and Individually Fair Clustering AISTATS 2022 Addressing fairness in classification with a model-agnostic multi-objective algorithm UAI 2021 Fair Sequential Selection Using Supervised Learning Models NeurIPS 2021 Justicia: A Stochastic SAT Approach to Formally Verify Fairness AAAI 2021 Data preprocessing to mitigate bias: A maximum entropy based approach ICML 2020 Deontological Ethics By Monotonicity Shape Constraints AISTATS 2020 Fairness constraints can help exact inference in structured prediction NeurIPS 2020 Pairwise Fairness for Ranking and Regression AAAI 2020 Fair Regression: Quantitative Definitions and Reduction-Based Algorithms ICML 2019