Group-based Fair Learning Leads to Counter-intuitive Predictions

4 October 2019

Papers citing "Group-based Fair Learning Leads to Counter-intuitive Predictions"

7 / 7 papers shown

Title
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals Andrew Cotter Heinrich Jiang S. Wang Taman Narayan Maya R. Gupta Seungil You Karthik Sridharan 79 157 0 11 Sep 2018
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 227 1,102 0 06 Mar 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 300 2,120 0 24 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 230 4,329 0 07 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores Jon M. Kleinberg S. Mullainathan Manish Raghavan FaML 121 1,775 0 19 Sep 2016
Satisfying Real-world Goals with Dataset Constraints Gabriel Goh Andrew Cotter Maya R. Gupta M. Friedlander OffRL 60 215 0 24 Jun 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