AI RESEARCH
Unifying On- and Off-Policy Variance Reduction Methods
arXiv CS.LG
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ArXi:2603.08370v1 Announce Type: cross 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.