Bandit Regret Scaling with the Effective Loss Range

15 May 2017 Nicolò Cesa-Bianchi Ohad Shamir

We study how the regret guarantees of nonstochastic multi-armed bandits can be improved, if the effective range of the losses in each round is small (e.g. the maximal difference between two losses in a given round). Despite a recent impossibility result, we show how this can be made possible under certain mild additional assumptions, such as availability of rough estimates of the losses, or advance knowledge of the loss of a single, possibly unspecified arm... (read more)

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