Fair Classifiers that Abstain without Harm

Fair Classifiers that Abstain without Harm

9 October 2023

Jean-François Ton

Yang Liu

Papers citing "Fair Classifiers that Abstain without Harm"

10 / 10 papers shown

Title
Classification with abstention but without disparities Nicolas Schreuder Evgenii Chzhen FaML 75 23 0 24 Feb 2021
Selective Classification Can Magnify Disparities Across Groups Erik Jones Shiori Sagawa Pang Wei Koh Ananya Kumar Percy Liang 79 47 0 27 Oct 2020
Consistent Estimators for Learning to Defer to an Expert Hussein Mozannar David Sontag 49 202 0 02 Jun 2020
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias Rachel K. E. Bellamy Kuntal Dey Michael Hind Samuel C. Hoffman Stephanie Houde ... Diptikalyan Saha P. Sattigeri Moninder Singh Kush R. Varshney Yunfeng Zhang FaML SyDa 96 806 0 03 Oct 2018
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 224 1,100 0 06 Mar 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 379 681 0 17 Feb 2018
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer David Madras T. Pitassi R. Zemel FaML 158 221 0 17 Nov 2017
Selective Classification for Deep Neural Networks Yonatan Geifman Ran El-Yaniv CVBM 92 526 0 23 May 2017
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 222 4,307 0 07 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores Jon M. Kleinberg S. Mullainathan Manish Raghavan FaML 114 1,769 0 19 Sep 2016