Characterizing Bias in Post-Bandit Inference under Index Algorithms
Bandit algorithms generate data for downstream inference, but adaptive sampling biases post-bandit sample means. We analyze this bias for stable index algorithms, including UCB1 and its generalizations, and derive sharp leading-order expressions for the sample-mean bias and expected $Z$-statistic. Our characterization...
Lisu Wang, Yilun Chen, Jiaqi Lu
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