Learning Fair Representations for Kernel Models

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Learning Fair Representations for Kernel Models

27 June 2019

Matt Fredrikson

Ameet Talwalkar

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Papers citing "Learning Fair Representations for Kernel Models"

10 / 10 papers shown

Title
Learning Fair and Transferable Representations L. Oneto Michele Donini Andreas Maurer Massimiliano Pontil FaML 71 19 0 25 Jun 2019
General Fair Empirical Risk Minimization L. Oneto Michele Donini Massimiliano Pontil FaML 64 39 0 29 Jan 2019
Empirical Risk Minimization under Fairness Constraints Michele Donini L. Oneto Shai Ben-David John Shawe-Taylor Massimiliano Pontil FaML 78 445 0 23 Feb 2018
Learning Integral Representations of Gaussian Processes Zilong Tan S. Mukherjee GP 28 2 0 21 Feb 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 382 684 0 17 Feb 2018
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
The Variational Fair Autoencoder Christos Louizos Kevin Swersky Yujia Li Max Welling R. Zemel DRL 223 636 0 03 Nov 2015
Certifying and removing disparate impact Michael Feldman Sorelle A. Friedler John Moeller C. Scheidegger Suresh Venkatasubramanian FaML 204 1,993 0 11 Dec 2014