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arXiv · 2508.14311

Online Learning with Multiple Fairness Regularizers via Graph-Structured Feedback

Quan Zhou·Jakub Marecek·Robert Shorten
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Abstract

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.

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Quan Zhou, Jakub Marecek, Robert Shorten. 2025-08-19. Online Learning with Multiple Fairness Regularizers via Graph-Structured Feedback. https://arxiv.org/abs/2508.14311

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