Fairness in Machine Learning: A Survey

4 October 2020

Papers citing "Fairness in Machine Learning: A Survey"

47 / 147 papers shown

Title
Fair Clustering Through Fairlets Flavio Chierichetti Ravi Kumar Silvio Lattanzi Sergei Vassilvitskii FaML 75 437 0 15 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 109 648 0 13 Feb 2018
Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making Michael Veale Max Van Kleek Reuben Binns 71 424 0 03 Feb 2018
Mitigating Unwanted Biases with Adversarial Learning B. Zhang Blake Lemoine Margaret Mitchell FaML 204 1,393 0 22 Jan 2018
Interventions over Predictions: Reframing the Ethical Debate for Actuarial Risk Assessment Chelsea Barabas Karthik Dinakar Joichi Ito M. Virza Jonathan Zittrain 119 144 0 21 Dec 2017
Calibration for the (Computationally-Identifiable) Masses Úrsula Hébert-Johnson Michael P. Kim Omer Reingold G. Rothblum FaML 75 88 0 22 Nov 2017
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness Michael Kearns Seth Neel Aaron Roth Zhiwei Steven Wu FaML 202 784 0 14 Nov 2017
Fair Kernel Learning Adrián Pérez-Suay Valero Laparra Gonzalo Mateo-García Jordi Munoz-Marí L. Gómez-Chova Gustau Camps-Valls FaML 69 84 0 16 Oct 2017
Fairness Testing: Testing Software for Discrimination Sainyam Galhotra Yuriy Brun A. Meliou 69 380 0 11 Sep 2017
On Fairness and Calibration Geoff Pleiss Manish Raghavan Felix Wu Jon M. Kleinberg Kilian Q. Weinberger FaML 207 882 0 06 Sep 2017
Fair Pipelines Amanda Bower Sarah Kitchen Laura Niss Martin Strauss Alexander Vargas Suresh Venkatasubramanian FaML 71 45 0 03 Jul 2017
Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations Alex Beutel Jilin Chen Zhe Zhao Ed H. Chi FaML 111 442 0 01 Jul 2017
Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American English Su Lin Blodgett Brendan O'Connor 82 148 0 30 Jun 2017
Fairer and more accurate, but for whom? Alexandra Chouldechova M. G'Sell 71 63 0 30 Jun 2017
Runaway Feedback Loops in Predictive Policing D. Ensign Sorelle A. Friedler Scott Neville C. Scheidegger Suresh Venkatasubramanian 65 347 0 29 Jun 2017
Avoiding Discrimination through Causal Reasoning Niki Kilbertus Mateo Rojas-Carulla Giambattista Parascandolo Moritz Hardt Dominik Janzing Bernhard Schölkopf FaML CML 115 584 0 08 Jun 2017
A Convex Framework for Fair Regression R. Berk Hoda Heidari S. Jabbari Matthew Joseph Michael Kearns Jamie Morgenstern Seth Neel Aaron Roth FaML 125 342 0 07 Jun 2017
Fair Inference On Outcomes Razieh Nabi I. Shpitser FaML 89 354 0 29 May 2017
The cost of fairness in classification A. Menon Robert C. Williamson FaML 65 20 0 25 May 2017
Beyond Parity: Fairness Objectives for Collaborative Filtering Sirui Yao Bert Huang FaML 45 367 0 24 May 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,090 0 22 May 2017
Balanced Policy Evaluation and Learning Nathan Kallus CML OffRL 437 142 0 21 May 2017
Fairness in Criminal Justice Risk Assessments: The State of the Art R. Berk Hoda Heidari S. Jabbari Michael Kearns Aaron Roth 66 1,001 0 27 Mar 2017
Counterfactual Fairness Matt J. Kusner Joshua R. Loftus Chris Russell Ricardo M. A. Silva FaML 230 1,587 0 20 Mar 2017
Simple rules for complex decisions Jongbin Jung Connor Concannon Ravi Shroff Sharad Goel D. Goldstein CML 62 105 0 15 Feb 2017
Identifying Significant Predictive Bias in Classifiers Zhe Zhang Daniel B. Neill 77 63 0 24 Nov 2016
Learning to Pivot with Adversarial Networks Gilles Louppe Michael Kagan Kyle Cranmer 76 227 0 03 Nov 2016
Fair Algorithms for Infinite and Contextual Bandits Matthew Joseph Michael Kearns Jamie Morgenstern Seth Neel Aaron Roth FedML FaML 67 56 0 29 Oct 2016
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment Muhammad Bilal Zafar Isabel Valera Manuel Gomez Rodriguez Krishna P. Gummadi FaML 208 1,214 0 26 Oct 2016
A statistical framework for fair predictive algorithms K. Lum J. Johndrow FaML 330 105 0 25 Oct 2016
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 302 2,131 0 24 Oct 2016
How to be Fair and Diverse? L. E. Celis Amit Deshpande Tarun Kathuria Nisheeth K. Vishnoi FaML 78 80 0 23 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 236 4,341 0 07 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores Jon M. Kleinberg S. Mullainathan Manish Raghavan FaML 122 1,783 0 19 Sep 2016
Semantics derived automatically from language corpora contain human-like biases Aylin Caliskan J. Bryson Arvind Narayanan 223 2,678 0 25 Aug 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 114 3,159 0 21 Jul 2016
Satisfying Real-world Goals with Dataset Constraints Gabriel Goh Andrew Cotter Maya R. Gupta M. Friedlander OffRL 70 215 0 24 Jun 2016
The Mythos of Model Interpretability Zachary Chase Lipton FaML 183 3,716 0 10 Jun 2016
Fairness in Learning: Classic and Contextual Bandits Matthew Joseph Michael Kearns Jamie Morgenstern Aaron Roth FaML 66 477 0 23 May 2016
Auditing Black-box Models for Indirect Influence Philip Adler Casey Falk Sorelle A. Friedler Gabriel Rybeck C. Scheidegger Brandon Smith Suresh Venkatasubramanian TDI MLAU 170 291 0 23 Feb 2016
A Confidence-Based Approach for Balancing Fairness and Accuracy Benjamin Fish Jeremy Kun Á. Lelkes FaML 216 248 0 21 Jan 2016
Censoring Representations with an Adversary Harrison Edwards Amos Storkey AAML FaML 74 506 0 18 Nov 2015
On the relation between accuracy and fairness in binary classification Indrė Žliobaitė FaML 80 198 0 21 May 2015
Interpretable Classification Models for Recidivism Prediction J. Zeng Berk Ustun Cynthia Rudin FaML 106 247 0 26 Mar 2015
Certifying and removing disparate impact Michael Feldman Sorelle A. Friedler John Moeller C. Scheidegger Suresh Venkatasubramanian FaML 212 1,996 0 11 Dec 2014
Generative Adversarial Networks Ian Goodfellow Jean Pouget-Abadie M. Berk Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville Yoshua Bengio GAN 148 2,198 0 10 Jun 2014
Almost-everywhere algorithmic stability and generalization error S. Kutin P. Niyogi 107 173 0 12 Dec 2012