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Exploration by Optimisation in Partial Monitoring (1907.05772v3)

Published 12 Jul 2019 in cs.LG, math.OC, and stat.ML

Abstract: We provide a simple and efficient algorithm for adversarial $k$-action $d$-outcome non-degenerate locally observable partial monitoring game for which the $n$-round minimax regret is bounded by $6(d+1) k{3/2} \sqrt{n \log(k)}$, matching the best known information-theoretic upper bound. The same algorithm also achieves near-optimal regret for full information, bandit and globally observable games.

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