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News/Price of Fairness in Bandits: A Tight Minimax Characterization
arxiv
PublishedJuly 16, 2026 at 4:00 AM
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Price of Fairness in Bandits: A Tight Minimax Characterization

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arXiv:2607.13402v1 Announce Type: cross Abstract: In bandit problems, standard regret-minimizing algorithms treat exploration as an amortized cost, which can expose early participants to unfair ex-ante losses in settings such as clinical trials. Recent work addresses this by evaluating the sequence

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