Recovering from Biased Data: Can Fairness Constraints Improve Accuracy?

2 December 2019

Papers citing "Recovering from Biased Data: Can Fairness Constraints Improve Accuracy?"

10 / 10 papers shown

Title
Efficient Fair Principal Component Analysis Mohammad Mahdi Kamani Farzin Haddadpour R. Forsati M. Mahdavi 71 37 0 12 Nov 2019
Identifying and Correcting Label Bias in Machine Learning Heinrich Jiang Ofir Nachum FaML 93 283 0 15 Jan 2019
Avoiding Disparity Amplification under Different Worldviews Samuel Yeom Michael Carl Tschantz 45 20 0 26 Aug 2018
Learning under selective labels in the presence of expert consistency Maria De-Arteaga A. Dubrawski Alexandra Chouldechova 27 37 0 02 Jul 2018
Selection Problems in the Presence of Implicit Bias Jon M. Kleinberg Manish Raghavan 55 93 0 04 Jan 2018
On Fairness and Calibration Geoff Pleiss Manish Raghavan Felix Wu Jon M. Kleinberg Kilian Q. Weinberger FaML 200 880 0 06 Sep 2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 302 2,120 0 24 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 233 4,330 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
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings Tolga Bolukbasi Kai-Wei Chang James Zou Venkatesh Saligrama Adam Kalai CVBM FaML 112 3,148 0 21 Jul 2016