Towards Model-Agnostic Post-Hoc Adjustment for Balancing Ranking
Fairness and Algorithm Utility

v1v2v3v4 (latest)

Towards Model-Agnostic Post-Hoc Adjustment for Balancing Ranking Fairness and Algorithm Utility

15 June 2020

Changshui Zhang

ArXiv (abs)PDF HTML

Papers citing "Towards Model-Agnostic Post-Hoc Adjustment for Balancing Ranking Fairness and Algorithm Utility"

11 / 11 papers shown

Title
Pairwise Fairness for Ranking and Regression Harikrishna Narasimhan Andrew Cotter Maya R. Gupta S. Wang 78 114 0 12 Jun 2019
Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search S. Geyik Stuart Ambler K. Kenthapadi 92 383 0 30 Apr 2019
The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the xAUC Metric Nathan Kallus Angela Zhou 90 74 0 15 Feb 2019
Residual Unfairness in Fair Machine Learning from Prejudiced Data Nathan Kallus Angela Zhou FaML 176 136 0 07 Jun 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 379 684 0 17 Feb 2018
A comparative study of fairness-enhancing interventions in machine learning Sorelle A. Friedler C. Scheidegger Suresh Venkatasubramanian Sonam Choudhary Evan P. Hamilton Derek Roth FaML 109 645 0 13 Feb 2018
Multitask learning and benchmarking with clinical time series data Hrayr Harutyunyan Hrant Khachatrian David C. Kale Greg Ver Steeg Aram Galstyan OOD AI4TS 186 878 0 22 Mar 2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 300 2,114 0 24 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 230 4,312 0 07 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores Jon M. Kleinberg S. Mullainathan Manish Raghavan FaML 119 1,775 0 19 Sep 2016
Certifying and removing disparate impact Michael Feldman Sorelle A. Friedler John Moeller C. Scheidegger Suresh Venkatasubramanian FaML 201 1,992 0 11 Dec 2014

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.