Selective Regression Under Fairness Criteria

28 October 2021

Papers citing "Selective Regression Under Fairness Criteria"

36 / 36 papers shown

Title
Interpretable and Fair Mechanisms for Abstaining Classifiers Daphne Lenders Andrea Pugnana Roberto Pellungrini Toon Calders D. Pedreschi F. Giannotti FaML 117 1 0 24 Mar 2025
A Clarification of the Nuances in the Fairness Metrics Landscape Alessandro Castelnovo Riccardo Crupi Greta Greco D. Regoli Ilaria Giuseppina Penco A. Cosentini FaML 40 186 0 01 Jun 2021
Classification with abstention but without disparities Nicolas Schreuder Evgenii Chzhen FaML 60 23 0 24 Feb 2021
Understanding and Mitigating Accuracy Disparity in Regression Jianfeng Chi Yuan Tian Geoffrey J. Gordon Han Zhao 48 25 0 24 Feb 2021
A Maximal Correlation Approach to Imposing Fairness in Machine Learning Joshua K. Lee Yuheng Bu P. Sattigeri Yikang Shen G. Wornell Leonid Karlinsky Rogerio Feris FaML 29 16 0 30 Dec 2020
An example of prediction which complies with Demographic Parity and equalizes group-wise risks in the context of regression Evgenii Chzhen Nicolas Schreuder FaML 30 4 0 13 Nov 2020
Selective Classification Can Magnify Disparities Across Groups Erik Jones Shiori Sagawa Pang Wei Koh Ananya Kumar Percy Liang 79 47 0 27 Oct 2020
Environment Inference for Invariant Learning Elliot Creager J. Jacobsen R. Zemel OOD 57 382 0 14 Oct 2020
Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models Andrew Jesson Sören Mindermann Uri Shalit Y. Gal CML 40 74 0 01 Jul 2020
Regression with reject option and application to kNN Christophe Denis Mohamed Hebiri A. Zaoui 30 36 0 30 Jun 2020
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information Pengyu Cheng Weituo Hao Shuyang Dai Jiachang Liu Zhe Gan Lawrence Carin VLM 54 351 0 22 Jun 2020
Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks Like Hui M. Belkin UQCV AAML VLM 46 171 0 12 Jun 2020
Classification vs regression in overparameterized regimes: Does the loss function matter? Vidya Muthukumar Adhyyan Narang Vignesh Subramanian M. Belkin Daniel J. Hsu A. Sahai 75 151 0 16 May 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 298 931 0 02 Mar 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 525 4,323 0 23 Aug 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 168 2,218 0 05 Jul 2019
Fair Regression: Quantitative Definitions and Reduction-based Algorithms Alekh Agarwal Miroslav Dudík Zhiwei Steven Wu FaML 44 247 0 30 May 2019
General Fair Empirical Risk Minimization L. Oneto Michele Donini Massimiliano Pontil FaML 57 38 0 29 Jan 2019
SelectiveNet: A Deep Neural Network with an Integrated Reject Option Yonatan Geifman Ran El-Yaniv CVBM OOD 118 310 0 26 Jan 2019
Fairness risk measures Robert C. Williamson A. Menon FaML 129 140 0 24 Jan 2019
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias Rachel K. E. Bellamy Kuntal Dey Michael Hind Samuel C. Hoffman Stephanie Houde ... Diptikalyan Saha P. Sattigeri Moninder Singh Kush R. Varshney Yunfeng Zhang FaML SyDa 96 806 0 03 Oct 2018
Learning Optimal Fair Policies Razieh Nabi Daniel Malinsky I. Shpitser FaML 39 87 0 06 Sep 2018
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 192 1,099 0 06 Mar 2018
Mitigating Unwanted Biases with Adversarial Learning B. Zhang Blake Lemoine Margaret Mitchell FaML 150 1,380 0 22 Jan 2018
Fair Forests: Regularized Tree Induction to Minimize Model Bias Edward Raff Jared Sylvester S. Mills FaML 39 69 0 21 Dec 2017
Fair Kernel Learning Adrián Pérez-Suay Valero Laparra Gonzalo Mateo-García Jordi Munoz-Marí L. Gómez-Chova Gustau Camps-Valls FaML 57 84 0 16 Oct 2017
Two-stage Algorithm for Fairness-aware Machine Learning Junpei Komiyama Hajime Shimao FaML 44 22 0 13 Oct 2017
On Fairness and Calibration Geoff Pleiss Manish Raghavan Felix Wu Jon M. Kleinberg Kilian Q. Weinberger FaML 160 876 0 06 Sep 2017
Meta-learners for Estimating Heterogeneous Treatment Effects using Machine Learning Sören R. Künzel Jasjeet Sekhon Peter J. Bickel Bin Yu CML 138 921 0 12 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 107 342 0 07 Jun 2017
Selective Classification for Deep Neural Networks Yonatan Geifman Ran El-Yaniv CVBM 90 526 0 23 May 2017
Fairness in Criminal Justice Risk Assessments: The State of the Art R. Berk Hoda Heidari S. Jabbari Michael Kearns Aaron Roth 49 994 0 27 Mar 2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 295 2,109 0 24 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 179 4,301 0 07 Oct 2016
The Variational Fair Autoencoder Christos Louizos Kevin Swersky Yujia Li Max Welling R. Zemel DRL 190 633 0 03 Nov 2015
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 216 12,422 0 24 Jun 2012