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Non-trivial two-armed partial-monitoring games are bandits
Published 24 Aug 2011 in cs.LG | (1108.4961v1)
Abstract: We consider online learning in partial-monitoring games against an oblivious adversary. We show that when the number of actions available to the learner is two and the game is nontrivial then it is reducible to a bandit-like game and thus the minimax regret is $\Theta(\sqrt{T})$.
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