Probably Approximately Metric-Fair Learning

Probably Approximately Metric-Fair Learning

8 March 2018

Papers citing "Probably Approximately Metric-Fair Learning"

17 / 17 papers shown

Title
Surfacing Biases in Large Language Models using Contrastive Input Decoding G. Yona Or Honovich Itay Laish Roee Aharoni 27 11 0 12 May 2023
Identifying, measuring, and mitigating individual unfairness for supervised learning models and application to credit risk models Rasoul Shahsavarifar Jithu Chandran M. Inchiosa A. Deshpande Mario Schlener V. Gossain Yara Elias Vinaya Murali FaML 16 0 0 11 Nov 2022
Omnipredictors for Constrained Optimization Lunjia Hu Inbal Livni-Navon Omer Reingold Chutong Yang 28 14 0 15 Sep 2022
Towards a Responsible AI Development Lifecycle: Lessons From Information Security Erick Galinkin SILM 21 6 0 06 Mar 2022
SLIDE: a surrogate fairness constraint to ensure fairness consistency Kunwoong Kim Ilsang Ohn Sara Kim Yongdai Kim 35 4 0 07 Feb 2022
Learning fair representation with a parametric integral probability metric Dongha Kim Kunwoong Kim Insung Kong Ilsang Ohn Yongdai Kim FaML 25 16 0 07 Feb 2022
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 43 16 0 20 Sep 2021
Fairkit, Fairkit, on the Wall, Who's the Fairest of Them All? Supporting Data Scientists in Training Fair Models Brittany Johnson Jesse Bartola Rico Angell Katherine Keith Sam Witty S. Giguere Yuriy Brun FaML 33 18 0 17 Dec 2020
Aligning AI With Shared Human Values Dan Hendrycks Collin Burns Steven Basart Andrew Critch Jingkai Li D. Song Jacob Steinhardt 63 522 0 05 Aug 2020
Two Simple Ways to Learn Individual Fairness Metrics from Data Debarghya Mukherjee Mikhail Yurochkin Moulinath Banerjee Yuekai Sun FaML 26 96 0 19 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 15 39 0 26 May 2020
Abstracting Fairness: Oracles, Metrics, and Interpretability Cynthia Dwork Christina Ilvento G. Rothblum Pragya Sur FaML 25 5 0 04 Apr 2020
Metric Learning for Individual Fairness Christina Ilvento FaML 19 96 0 01 Jun 2019
Average Individual Fairness: Algorithms, Generalization and Experiments Michael Kearns Aaron Roth Saeed Sharifi-Malvajerdi FaML FedML 19 84 0 25 May 2019
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification Michael P. Kim Amirata Ghorbani James Zou MLAU 25 336 0 31 May 2018
Online Learning with an Unknown Fairness Metric Stephen Gillen Christopher Jung Michael Kearns Aaron Roth FaML 37 143 0 20 Feb 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,092 0 24 Oct 2016