Fair Representation Learning using Interpolation Enabled Disentanglement

31 July 2021

Papers citing "Fair Representation Learning using Interpolation Enabled Disentanglement"

20 / 20 papers shown

Title
Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination Tao Zhang Tianqing Zhu Jing Li Mengde Han Wanlei Zhou Philip S. Yu FaML 58 50 0 25 Sep 2020
Fairness by Learning Orthogonal Disentangled Representations Mhd Hasan Sarhan Nassir Navab Abouzar Eslami Shadi Albarqouni FaML OOD CML 81 97 0 12 Mar 2020
Auditing ML Models for Individual Bias and Unfairness Songkai Xue Mikhail Yurochkin Yuekai Sun MLAU 81 23 0 11 Mar 2020
Recovering from Biased Data: Can Fairness Constraints Improve Accuracy? Avrim Blum Kevin Stangl FaML 43 87 0 02 Dec 2019
Theory and Evaluation Metrics for Learning Disentangled Representations Kien Do T. Tran CoGe DRL 49 96 0 26 Aug 2019
Disentangling Influence: Using Disentangled Representations to Audit Model Predictions Charles Marx R. L. Phillips Sorelle A. Friedler C. Scheidegger Suresh Venkatasubramanian TDI CML MLAU 51 27 0 20 Jun 2019
Flexibly Fair Representation Learning by Disentanglement Elliot Creager David Madras J. Jacobsen Marissa A. Weis Kevin Swersky T. Pitassi R. Zemel FaML OOD 180 333 0 06 Jun 2019
CCMI : Classifier based Conditional Mutual Information Estimation Sudipto Mukherjee Himanshu Asnani Sreeram Kannan VLM 101 81 0 05 Jun 2019
On the Fairness of Disentangled Representations Francesco Locatello G. Abbati Tom Rainforth Stefan Bauer Bernhard Schölkopf Olivier Bachem FaML DRL 73 226 0 31 May 2019
Hunting for Discriminatory Proxies in Linear Regression Models Samuel Yeom Anupam Datta Matt Fredrikson 101 19 0 16 Oct 2018
Active Fairness in Algorithmic Decision Making Alejandro Noriega-Campero Michiel A. Bakker Bernardo Garcia-Bulle Alex Pentland FaML 49 85 0 28 Sep 2018
Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer David Berthelot Colin Raffel Aurko Roy Ian Goodfellow 52 264 0 19 Jul 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 373 681 0 17 Feb 2018
Disentangling by Factorising Hyunjik Kim A. Mnih CoGe OOD 62 1,346 0 16 Feb 2018
Mitigating Unwanted Biases with Adversarial Learning B. Zhang Blake Lemoine Margaret Mitchell FaML 181 1,380 0 22 Jan 2018
A Convex Framework for Fair Regression R. Berk Hoda Heidari S. Jabbari Matthew Joseph Michael Kearns Jamie Morgenstern Seth Neel Aaron Roth FaML 107 342 0 07 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.0K 21,815 0 22 May 2017
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment Muhammad Bilal Zafar Isabel Valera Manuel Gomez Rodriguez Krishna P. Gummadi FaML 184 1,205 0 26 Oct 2016
The Variational Fair Autoencoder Christos Louizos Kevin Swersky Yujia Li Max Welling R. Zemel DRL 217 633 0 03 Nov 2015
Certifying and removing disparate impact Michael Feldman Sorelle A. Friedler John Moeller C. Scheidegger Suresh Venkatasubramanian FaML 185 1,984 0 11 Dec 2014