Fast Fair Regression via Efficient Approximations of Mutual Information

14 February 2020

Papers citing "Fast Fair Regression via Efficient Approximations of Mutual Information"

10 / 10 papers shown

Title
Counterfactually Fair Regression with Double Machine Learning Patrick Rehill FaML 56 1 0 21 Mar 2023
Mean Parity Fair Regression in RKHS Shaokui Wei Jiayin Liu Bing Li H. Zha 48 3 0 21 Feb 2023
Practical Approaches for Fair Learning with Multitype and Multivariate Sensitive Attributes Tennison Liu Alex J. Chan B. V. Breugel M. Schaar FaML 53 2 0 11 Nov 2022
Fair Regression under Sample Selection Bias Wei Du Xintao Wu Hanghang Tong 56 4 0 08 Oct 2021
Gradual (In)Compatibility of Fairness Criteria Corinna Hertweck T. Raz 79 12 0 09 Sep 2021
Achieving Fairness with a Simple Ridge Penalty M. Scutari F. Panero M. Proissl FaML 87 14 0 18 May 2021
A Stochastic Optimization Framework for Fair Risk Minimization Andrew Lowy Sina Baharlouei Rakesh Pavan Meisam Razaviyayn Ahmad Beirami FaML 69 21 0 24 Feb 2021
Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation Yue Liu Yezhen Wang Shanghang Zhang Dongsheng Li Trevor Darrell Kurt Keutzer Han Zhao OOD 83 96 0 09 Oct 2020
A minimax framework for quantifying risk-fairness trade-off in regression Evgenii Chzhen Nicolas Schreuder FaML 111 34 0 28 Jul 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 69 40 0 26 May 2020