Empirical Likelihood for Contextual Bandits

NIPS 2020, 2020.

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We propose a tighter estimator for off-policy evaluation with improved statistical performance over previous proposals

Abstract:

We apply empirical likelihood techniques to contextual bandit policy value estimation, confidence intervals, and learning. We propose a tighter estimator for off-policy evaluation with improved statistical performance over previous proposals. Coupled with this estimator is a confidence interval which also improves over previous proposals....More
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