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Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

14 November 2017

Papers citing "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness"

48 / 448 papers shown

Title
Average Individual Fairness: Algorithms, Generalization and Experiments Michael Kearns Aaron Roth Saeed Sharifi-Malvajerdi FaML FedML 130 87 0 25 May 2019
Proportionally Fair Clustering Xingyu Chen Brandon Fain Charles Lyu Kamesh Munagala FedML FaML 130 144 0 09 May 2019
Fair Classification and Social Welfare Lily Hu Yiling Chen FaML 90 92 0 01 May 2019
Tracking and Improving Information in the Service of Fairness Sumegha Garg Michael P. Kim Omer Reingold FaML 60 13 0 22 Apr 2019
Introduction to Multi-Armed Bandits Aleksandrs Slivkins 704 1,025 0 15 Apr 2019
FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning Ángel Alexander Cabrera Will Epperson Fred Hohman Minsuk Kahng Jamie Morgenstern Duen Horng Chau FaML 139 187 0 10 Apr 2019
Preference-Informed Fairness Michael P. Kim Aleksandra Korolova G. Rothblum G. Yona FaML 126 41 0 03 Apr 2019
Multi-Differential Fairness Auditor for Black Box Classifiers Xavier Gitiaux Huzefa Rangwala FaML 60 7 0 18 Mar 2019
General Fair Empirical Risk Minimization L. Oneto Michele Donini Massimiliano Pontil FaML 110 40 0 29 Jan 2019
Identifying and Correcting Label Bias in Machine Learning Heinrich Jiang Ofir Nachum FaML 104 285 0 15 Jan 2019
Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements Alex Beutel Jilin Chen Tulsee Doshi Hai Qian Allison Woodruff Christine Luu Pierre Kreitmann Jonathan Bischof Ed H. Chi FaML 113 153 0 14 Jan 2019
What are the biases in my word embedding? Nathaniel Swinger Maria De-Arteaga IV NeilThomasHeffernan Mark D. M. Leiserson Adam Tauman Kalai 85 104 0 20 Dec 2018
Differentially Private Fair Learning Matthew Jagielski Michael Kearns Jieming Mao Alina Oprea Aaron Roth Saeed Sharifi-Malvajerdi Jonathan R. Ullman FaML FedML 118 150 0 06 Dec 2018
Adversarial Bandits with Knapsacks Nicole Immorlica Karthik Abinav Sankararaman Robert Schapire Aleksandrs Slivkins 213 116 0 28 Nov 2018
50 Years of Test (Un)fairness: Lessons for Machine Learning Ben Hutchinson Margaret Mitchell AILaw FaML 101 364 0 25 Nov 2018
How to Use Heuristics for Differential Privacy Seth Neel Aaron Roth Zhiwei Steven Wu 76 26 0 19 Nov 2018
Bayesian Modeling of Intersectional Fairness: The Variance of Bias James R. Foulds Rashidul Islam Kamrun Naher Keya Shimei Pan 68 41 0 18 Nov 2018
Aequitas: A Bias and Fairness Audit Toolkit Pedro Saleiro Benedict Kuester Loren Hinkson J. London Abby Stevens Ari Anisfeld Kit T. Rodolfa Rayid Ghani 160 329 0 14 Nov 2018
An exploration of algorithmic discrimination in data and classification Martin Wahl Jiuyong Li Feiyue Ye Lin Liu T. Le Ping Xiong 59 1 0 06 Nov 2018
FairMod - Making Predictive Models Discrimination Aware Jixue Liu Jiuyong Li Lin Liu T. Le Feiyue Ye Gefei Li 20 1 0 05 Nov 2018
On preserving non-discrimination when combining expert advice Avrim Blum Suriya Gunasekar Thodoris Lykouris Nathan Srebro FaML 65 29 0 28 Oct 2018
The Frontiers of Fairness in Machine Learning Alexandra Chouldechova Aaron Roth FaML 210 416 0 20 Oct 2018
From Soft Classifiers to Hard Decisions: How fair can we be? R. Canetti A. Cohen Nishanth Dikkala Govind Ramnarayan Sarah Scheffler Adam D. Smith FaML 160 60 0 03 Oct 2018
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk Stephen Pfohl Ben J. Marafino Adrien Coulet F. Rodriguez L. Palaniappan N. Shah 71 68 0 12 Sep 2018
Simplicity Creates Inequity: Implications for Fairness, Stereotypes, and Interpretability Jon M. Kleinberg S. Mullainathan 71 70 0 12 Sep 2018
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 96 158 0 11 Sep 2018
The implicit fairness criterion of unconstrained learning Lydia T. Liu Max Simchowitz Moritz Hardt FedML FaML 65 1 0 29 Aug 2018
An Empirical Study of Rich Subgroup Fairness for Machine Learning Michael Kearns Seth Neel Aaron Roth Zhiwei Steven Wu FaML 115 209 0 24 Aug 2018
An Intersectional Definition of Fairness James R. Foulds Rashidul Islam Kamrun Naher Keya Shimei Pan FaML 75 191 0 22 Jul 2018
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices Till Speicher Hoda Heidari Nina Grgic-Hlaca Krishna P. Gummadi Adish Singla Adrian Weller Muhammad Bilal Zafar FaML 109 265 0 02 Jul 2018
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints Andrew Cotter Maya R. Gupta Heinrich Jiang Nathan Srebro Karthik Sridharan S. Wang Blake E. Woodworth Seungil You FaML 109 106 0 29 Jun 2018
Fairness Without Demographics in Repeated Loss Minimization Tatsunori B. Hashimoto Megha Srivastava Hongseok Namkoong Percy Liang FaML 177 585 0 20 Jun 2018
Fairness Under Composition Cynthia Dwork Christina Ilvento FaML 119 127 0 15 Jun 2018
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification Michael P. Kim Amirata Ghorbani James Zou MLAU 248 346 0 31 May 2018
Metric-Optimized Example Weights Sen Zhao M. M. Fard Harikrishna Narasimhan Maya R. Gupta 40 17 0 27 May 2018
Fair Allocation of Indivisible Public Goods Brandon Fain Kamesh Munagala Nisarg Shah 79 115 0 08 May 2018
Two-Player Games for Efficient Non-Convex Constrained Optimization Andrew Cotter Heinrich Jiang Karthik Sridharan 107 118 0 17 Apr 2018
Unleashing Linear Optimizers for Group-Fair Learning and Optimization Daniel Alabi Nicole Immorlica Adam Tauman Kalai FedML FaML 73 27 0 11 Apr 2018
Probably Approximately Metric-Fair Learning G. Rothblum G. Yona FaML FedML 80 86 0 08 Mar 2018
Fairness Through Computationally-Bounded Awareness Michael P. Kim Omer Reingold G. Rothblum FaML 99 146 0 08 Mar 2018
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 245 1,108 0 06 Mar 2018
Empirical Risk Minimization under Fairness Constraints Michele Donini L. Oneto Shai Ben-David John Shawe-Taylor Massimiliano Pontil FaML 102 445 0 23 Feb 2018
Online Learning with an Unknown Fairness Metric Stephen Gillen Christopher Jung Michael Kearns Aaron Roth FaML 75 144 0 20 Feb 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 391 685 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 123 648 0 13 Feb 2018
Calibration for the (Computationally-Identifiable) Masses Úrsula Hébert-Johnson Michael P. Kim Omer Reingold G. Rothblum FaML 91 88 0 22 Nov 2017
Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation S. Tan R. Caruana Giles Hooker Yin Lou MLAU 148 188 0 17 Oct 2017
Fairness in Criminal Justice Risk Assessments: The State of the Art R. Berk Hoda Heidari S. Jabbari Michael Kearns Aaron Roth 68 1,001 0 27 Mar 2017