Unifying On- and Off-Policy Variance Reduction Methods
Continuous and efficient experimentation is key to the practical success of user-facing applications on the web, both through online A/B-tests and off-policy evaluation. Despite their shared objective -- estimating the incremental value of a treatment -- these domains often operate in isolation, utilising distinct terminologies and statistical toolkits. This paper bridges that divide by establishing a formal equivalence between their canonical variance reduction methods. We prove that the standard online Difference-in-Means estimator is mathematically identical to an off-policy Inverse Propensity Scoring estimator equipped with an optimal (variance-minimising) additive control variate. Ex...
| Authors | Olivier Jeunen |
|---|---|
| Primary category | stat.ML |
| Published | 9 March 2026 |
| Last updated at source | 9 March 2026 |
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