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Precise Asymptotics and Refined Regret of Variance-Aware UCB
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Gives an asymptotic characterization of arm-pulling rates for the variance-aware UCB-V bandit algorithm, extending recent canonical-UCB results to refine its regret analysis.
Problem
Understanding the precise asymptotic arm-pulling behavior and regret of UCB-V, a variance-aware variant of UCB, for multi-armed bandits.
Approach
Extends recent asymptotic characterizations of canonical UCB arm-pulling rates to UCB-V, which incorporates variance estimates, yielding refined regret characterization.
Experimental setup
Metrics: arm-pulling rates regret
Builds on: UCB-V UCB
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