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$α$-Fair Contextual Bandits
In this paper, we consider the $\alpha$-Fair Contextual Bandits problem, where the objective is to maximize the global $\alpha$-fair utility function - a non-decreasing concave function of the cumulative rewards in the adversarial setting.
Online Subset Selection using $α$-Core with no Augmented Regret
In this connection, we propose an online learning policy called SCore (Subset Selection with Core) that solves the problem for a large class of reward functions.
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