Title
Fairness Practices in Industry: A Case Study in Machine Learning Teams Building Recommender Systems Jing Nathan Yan Junxiong Wang Jeffrey M. Rzeszotarski Allison Koenecke FaML 81 0 0 26 May 2025
Enforcing Fairness Where It Matters: An Approach Based on Difference-of-Convex Constraints Yutian He Yankun Huang Yao Yao Qihang Lin FaML 53 0 0 18 May 2025
Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification Daniel Borkan Lucas Dixon Jeffrey Scott Sorensen Nithum Thain Lucy Vasserman 92 493 0 11 Mar 2019
Degenerate Feedback Loops in Recommender Systems Ray Jiang Silvia Chiappa Tor Lattimore András Gyorgy Pushmeet Kohli 54 196 0 27 Feb 2019
Policy Learning for Fairness in Ranking Ashudeep Singh Thorsten Joachims OffRL 90 219 0 11 Feb 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 98 153 0 14 Jan 2019
Top-K Off-Policy Correction for a REINFORCE Recommender System Minmin Chen Alex Beutel Paul Covington Sagar Jain Francois Belletti Ed H. Chi CML OffRL 143 483 0 06 Dec 2018
Seq2Slate: Re-ranking and Slate Optimization with RNNs Irwan Bello Sayali Kulkarni Sagar Jain Craig Boutilier Ed H. Chi Elad Eban Xiyang Luo Alan Mackey Ofer Meshi 123 93 0 04 Oct 2018
Exploring Author Gender in Book Rating and Recommendation Michael D. Ekstrand Daniel Kluver FaML 61 115 0 22 Aug 2018
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 230 1,105 0 06 Mar 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 384 685 0 17 Feb 2018
Mitigating Unwanted Biases with Adversarial Learning B. Zhang Blake Lemoine Margaret Mitchell FaML 204 1,393 0 22 Jan 2018
Selection Problems in the Presence of Implicit Bias Jon M. Kleinberg Manish Raghavan 64 93 0 04 Jan 2018
On Fairness and Calibration Geoff Pleiss Manish Raghavan Felix Wu Jon M. Kleinberg Kilian Q. Weinberger FaML 205 880 0 06 Sep 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
On conditional parity as a notion of non-discrimination in machine learning Yaácov Ritov Yuekai Sun Ruofei Zhao 49 40 0 26 Jun 2017
Beyond Parity: Fairness Objectives for Collaborative Filtering Sirui Yao Bert Huang FaML 45 367 0 24 May 2017
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
Unbiased Learning-to-Rank with Biased Feedback Thorsten Joachims Adith Swaminathan Tobias Schnabel CML 95 541 0 16 Aug 2016
Satisfying Real-world Goals with Dataset Constraints Gabriel Goh Andrew Cotter Maya R. Gupta M. Friedlander OffRL 70 215 0 24 Jun 2016
Unbiased Comparative Evaluation of Ranking Functions Tobias Schnabel Adith Swaminathan P. Frazier Thorsten Joachims 60 27 0 25 Apr 2016
Recommendations as Treatments: Debiasing Learning and Evaluation Tobias Schnabel Adith Swaminathan Ashudeep Singh Navin Chandak Thorsten Joachims CML 166 686 0 17 Feb 2016
Censoring Representations with an Adversary Harrison Edwards Amos Storkey AAML FaML 74 506 0 18 Nov 2015
The Variational Fair Autoencoder Christos Louizos Kevin Swersky Yujia Li Max Welling R. Zemel DRL 225 636 0 03 Nov 2015
Ranking via Sinkhorn Propagation Ryan P. Adams R. Zemel 110 148 0 09 Jun 2011