Proposes an A/B testing estimator that introduces a hypothetical middle algorithm for stepwise estimation to induce positive correlation, reducing selection errors and halving required data volume.
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2026 1verdicts
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A More Accurate Algorithm Comparison through A/B Testing using Offline Evaluation Methods
Proposes an A/B testing estimator that introduces a hypothetical middle algorithm for stepwise estimation to induce positive correlation, reducing selection errors and halving required data volume.