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Optimal Multi-way Decision Trees for Stratified Sampling in Online Controlled Experiments
Online controlled experiments, or A/B tests, are widely used to estimate causal effects on digital platforms. A central challenge is to improve experimental sensitivity, or statistical power, without increasing the experimental sample size. Stratified sampling is a classical variance reduction techn
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