Fair Algorithms for Infinite and Contextual Bandits

Fair Algorithms for Infinite and Contextual Bandits

29 October 2016

Jamie Morgenstern

Papers citing "Fair Algorithms for Infinite and Contextual Bandits"

12 / 12 papers shown

Title
Improved Regret Bounds for Online Fair Division with Bandit Learning Benjamin G. Schiffer Shirley Zhang 36 0 0 13 Jan 2025
Honor Among Bandits: No-Regret Learning for Online Fair Division Ariel D. Procaccia Benjamin Schiffer Shirley Zhang FaML 21 2 0 01 Jul 2024
Counterfactual Fairness for Predictions using Generative Adversarial Networks Yuchen Ma Dennis Frauen Valentyn Melnychuk Stefan Feuerriegel 31 2 0 26 Oct 2023
Socially Fair Reinforcement Learning Debmalya Mandal Jiarui Gan OffRL 20 13 0 26 Aug 2022
Entropy Regularization for Population Estimation Ben Chugg Peter Henderson Jacob Goldin Daniel E. Ho 26 3 0 24 Aug 2022
Survey on Fair Reinforcement Learning: Theory and Practice Pratik Gajane A. Saxena M. Tavakol George Fletcher Mykola Pechenizkiy FaML OffRL 35 13 0 20 May 2022
Fairness of Exposure in Stochastic Bandits Lequn Wang Yiwei Bai Wen Sun Thorsten Joachims FaML 16 48 0 03 Mar 2021
Combinatorial Sleeping Bandits with Fairness Constraints Fengjiao Li Jia-Wei Liu Bo Ji 17 159 0 15 Jan 2019
Online Learning with an Unknown Fairness Metric Stephen Gillen Christopher Jung Michael Kearns Aaron Roth FaML 19 143 0 20 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 23 635 0 13 Feb 2018
Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American English Su Lin Blodgett Brendan T. O'Connor 22 145 0 30 Jun 2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,082 0 24 Oct 2016