In this way, counterfactual estimators enable Off-policy Evaluation (OPE) akin to an unbiased offline A/B test, as well as learning new decision-making policies through Off-policy Learning (OPL).

In this way, counterfactual estimators enable Off-policy Evaluation (OPE) akin to an unbiased offline A/B test, as well as learning new recommendation policies through Off-policy Learning...

Sep 13, 2021 · In this way, counterfactual estimators enable Off-policy Evaluation (OPE) akin to an unbiased offline A/B test, as well as learning new recommendation policies through Off-policy Learning (OPL). The goal of this tutorial is to summarize Foundations, Implementations, and Recent Advances of OPE/OPL.

In this way, counterfactual estimators enable Off-policy Evaluation (OPE) akin to an unbiased offline A/B test, as well as learning new recommendation policies through Off-policy Learning (OPL). The goal of this tutorial is to summarize Foundations, Implementations, and Recent Advances of OPE/OPL.

In this way, counterfactual estimators enable Off-policy Evaluation (OPE) akin to an unbiased offline A/B test, as well as learning new recommendation policies through Off-policy Learning (OPL). The goal of this tutorial is to summarize Foundations, Implementations, and Recent Advances of OPE/OPL.

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