On the Complexity of A/B Testing

13 May 2014Emilie KaufmannOlivier CappéAurélien Garivier

A/B testing refers to the task of determining the best option among two alternatives that yield random outcomes. We provide distribution-dependent lower bounds for the performance of A/B testing that improve over the results currently available both in the fixed-confidence (or delta-PAC) and fixed-budget settings... (read more)

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