Feb. 9, 2024, 5:42 a.m. | Subham Pokhriyal Shweta Jain Ganesh Ghalme Swapnil Dhamal Sujit Gujar

cs.LG updates on arXiv.org arxiv.org

Existing approaches to fairness in stochastic multi-armed bandits (MAB) primarily focus on exposure guarantee to individual arms. When arms are naturally grouped by certain attribute(s), we propose Bi-Level Fairness, which considers two levels of fairness. At the first level, Bi-Level Fairness guarantees a certain minimum exposure to each group. To address the unbalanced allocation of pulls to individual arms within a group, we consider meritocratic fairness at the second level, which ensures that each arm is pulled according to its …

cs.ai cs.cy cs.lg cs.ma fairness focus multi-armed bandits stochastic

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