mlsanityData to 14 Oct 2026

Online Learning with Multiple Fairness Regularizers via Graph-Structured Feedback

arXiv 2508.14311 ↗First posted 19 Aug 2025cs.LG cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

There is an increasing need to enforce multiple, often competing, measures of fairness within automated decision systems. The appropriate weighting of these fairness objectives is typically unknown a priori, may change over time and, in our setting, must be learned adaptively through sequential interactions. In this work, we address this challenge in a bandit setting, where decisions are made with graph-structured feedback.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 23 of its 46 references that are in the map. First posted on arXiv 19 Aug 2025.

Builds on

23 of 46 references.

References · 23

  1. 2016Equality of Opportunity in Supervised Learningcited by 2,007
  2. 2017Counterfactual Fairnesscited by 804
  3. 2016CVXPY: A Python-Embedded Modeling Language for Convex Optimizationcited by 641
  4. 2018Delayed Impact of Fair Machine Learningcited by 184
  5. 2016Fairness in Reinforcement Learningcited by 95
  6. 2015Online Learning with Feedback Graphs: Beyond Banditscited by 80
  7. 2018Bias Mitigation Post-processing for Individual and Group Fairnesscited by 72
  8. 2014Nonstochastic Multi-Armed Bandits with Graph-Structured Feedbackcited by 61
  9. 2019Algorithms for Fairness in Sequential Decision Makingcited by 56
  10. 2020Dual Mirror Descent for Online Allocation Problemscited by 52
  11. 2013From Bandits to Experts: A Tale of Domination and Independencecited by 28
  12. 2016Online Learning with Feedback Graphs Without the Graphscited by 27
11 more
  1. 2017Information Directed Sampling for Stochastic Bandits with Graph Feedbackcited by 24
  2. 2019Feedback graph regret bounds for Thompson Sampling and UCBcited by 17
  3. 2019Bandits with Feedback Graphs and Switching Costscited by 17
  4. 2021Understanding Bandits with Graph Feedbackcited by 14
  5. 2020Beyond Individual and Group Fairnesscited by 13
  6. 2019Stochastic Online Learning with Probabilistic Graph Feedbackcited by 12
  7. 2017Thompson Sampling For Stochastic Bandits with Graph Feedbackcited by 9
  8. 2018Analysis of Thompson Sampling for Graphical Bandits Without the Graphscited by 7
  9. 2022Individually Fair Learning with One-Sided Feedbackcited by 5
  10. 2021Time-Varying Optimization of Networked Systems with Human Preferencescited by 4
  11. 2024Efficient Fairness-Performance Pareto Front Computationcited by 3

Built on by

Not cited yet.