Robust Optimization for Fairness with Noisy Protected Groups

21 February 2020

S. Wang

Wenshuo Guo

Harikrishna Narasimhan

Papers citing "Robust Optimization for Fairness with Noisy Protected Groups"

29 / 29 papers shown

Title
Specification Overfitting in Artificial Intelligence Benjamin Roth Pedro Henrique Luz de Araujo Yuxi Xia Saskia Kaltenbrunner Christoph Korab 86 1 0 13 Mar 2024
Fairness Risks for Group-conditionally Missing Demographics Kaiqi Jiang Wenzhe Fan Mao Li Xinhua Zhang 114 0 0 20 Feb 2024
Fairness without Demographics through Adversarially Reweighted Learning Preethi Lahoti Alex Beutel Jilin Chen Kang Lee Flavien Prost Nithum Thain Xuezhi Wang Ed H. Chi FaML 90 333 0 23 Jun 2020
Fair Learning with Private Demographic Data Hussein Mozannar Mesrob I. Ohannessian Nathan Srebro 40 75 0 26 Feb 2020
Deontological Ethics By Monotonicity Shape Constraints S. Wang Maya R. Gupta 38 21 0 31 Jan 2020
Measurement and Fairness Abigail Z. Jacobs Hanna M. Wallach 44 383 0 11 Dec 2019
A First-Order Algorithmic Framework for Wasserstein Distributionally Robust Logistic Regression Jiajin Li Sen Huang Anthony Man-Cho So OOD 37 13 0 28 Oct 2019
Pairwise Fairness for Ranking and Regression Harikrishna Narasimhan Andrew Cotter Maya R. Gupta S. Wang 45 114 0 12 Jun 2019
Equalized odds postprocessing under imperfect group information Pranjal Awasthi Matthäus Kleindessner Jamie Morgenstern 40 90 0 07 Jun 2019
Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination Nathan Kallus Xiaojie Mao Angela Zhou FaML 34 156 0 01 Jun 2019
Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making S. Aghaei Javad Azizi P. Vayanos FaML 13 177 0 25 Mar 2019
Noise-tolerant fair classification A. Lamy Ziyuan Zhong A. Menon Nakul Verma NoLa 35 76 0 30 Jan 2019
Fair Algorithms for Clustering Suman Kalyan Bera Deeparnab Chakrabarty Nicolas J. Flores Maryam Negahbani FaML FedML 44 233 0 08 Jan 2019
50 Years of Test (Un)fairness: Lessons for Machine Learning Ben Hutchinson Margaret Mitchell AILaw FaML 32 357 0 25 Nov 2018
Learning Models with Uniform Performance via Distributionally Robust Optimization John C. Duchi Hongseok Namkoong OOD 39 413 0 20 Oct 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 51 154 0 11 Sep 2018
Proxy Fairness Maya R. Gupta Andrew Cotter M. M. Fard S. Wang 34 71 0 28 Jun 2018
Fairness Without Demographics in Repeated Loss Minimization Tatsunori B. Hashimoto Megha Srivastava Hongseok Namkoong Percy Liang FaML 49 581 0 20 Jun 2018
Two-Player Games for Efficient Non-Convex Constrained Optimization Andrew Cotter Heinrich Jiang Karthik Sridharan 27 118 0 17 Apr 2018
Delayed Impact of Fair Machine Learning Lydia T. Liu Sarah Dean Esther Rolf Max Simchowitz Moritz Hardt FaML 56 475 0 12 Mar 2018
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 74 1,094 0 06 Mar 2018
Empirical Risk Minimization under Fairness Constraints Michele Donini L. Oneto Shai Ben-David John Shawe-Taylor Massimiliano Pontil FaML 65 443 0 23 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 73 639 0 13 Feb 2018
A Convex Framework for Fair Regression R. Berk Hoda Heidari S. Jabbari Matthew Joseph Michael Kearns Jamie Morgenstern Seth Neel Aaron Roth FaML 92 342 0 07 Jun 2017
Counterfactual Fairness Matt J. Kusner Joshua R. Loftus Chris Russell Ricardo M. A. Silva FaML 174 1,566 0 20 Mar 2017
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 65 4,276 0 07 Oct 2016
Scalable Learning of Non-Decomposable Objectives Elad Eban Mariano Schain Alan Mackey A. Gordon R. Rifkin G. Elidan 22 109 0 16 Aug 2016
Satisfying Real-world Goals with Dataset Constraints Gabriel Goh Andrew Cotter Maya R. Gupta M. Friedlander OffRL 34 215 0 24 Jun 2016
Data-driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations Peyman Mohajerin Esfahani Daniel Kuhn 39 1,641 0 19 May 2015