A minimax framework for quantifying risk-fairness trade-off in regression

28 July 2020

Papers citing "A minimax framework for quantifying risk-fairness trade-off in regression"

12 / 12 papers shown

Title
Liouville PDE-based sliced-Wasserstein flow for fair regression Pilhwa Lee Jayshawn Cooper 61 0 0 22 May 2025
Enforcing Fairness Where It Matters: An Approach Based on Difference-of-Convex Constraints Yutian He Yankun Huang Yao Yao Qihang Lin FaML 47 0 0 18 May 2025
Multi-Output Distributional Fairness via Post-Processing Gang Li Qihang Lin Ayush Ghosh Tianbao Yang 108 0 0 31 Aug 2024
Fair Regression with Wasserstein Barycenters Evgenii Chzhen Christophe Denis Mohamed Hebiri L. Oneto Massimiliano Pontil 56 106 0 12 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 36 40 0 26 May 2020
Rényi Fair Inference Sina Baharlouei Maher Nouiehed Ahmad Beirami Meisam Razaviyayn FaML 47 67 0 28 Jun 2019
The limits of distribution-free conditional predictive inference Rina Foygel Barber Emmanuel J. Candès Aaditya Ramdas Robert Tibshirani UQCV 259 273 0 12 Mar 2019
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 171 1,094 0 06 Mar 2018
Empirical Risk Minimization under Fairness Constraints Michele Donini L. Oneto Shai Ben-David John Shawe-Taylor Massimiliano Pontil FaML 76 443 0 23 Feb 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 345 678 0 17 Feb 2018
Existence and Consistency of Wasserstein Barycenters Thibaut Le Gouic Jean-Michel Loubes 47 130 0 12 Jun 2015
Robust linear least squares regression Jean-Yves Audibert O. Catoni 100 99 0 01 Oct 2010