Quantile Off-Policy Evaluation via Deep Conditional Generative Learning

Understand

Off-Policy evaluation (OPE) is concerned with evaluating a new target policy using offline data generated by a potentially different behavior policy.

• It is critical in a number of sequential decision making problems ranging from healthcare to technology industries.
• Most of the work in existing literature is focused on evaluating the mean outcome of a given policy, and ignores the variability of the outcome.
• However, in a variety of applications, criteria other than the mean may be more sensible.