Adaptive strategy for stratified Monte Carlo sampling

Abstract

We consider the problem of stratified sampling for Monte Carlo integration of a random variable. We model this problem in a K-armed bandit, where the arms represent the K strata. The goal is to estimate the integral mean, that is a weighted average of the mean values of the arms. The learner is allowed to sample the variable n times, but it can decide on… (More)

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