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Trading Regret Rate for Computational Efficiency in Online Learning with Limited Feedback
Published on 2009-08-263129 Views
We study low regret algorithms for online learning with limited feedback, where there is an additional constraint on the computational power of the learner. Focusing on multi-armed bandit with side in