Review for NeurIPS paper: Minimax Value Interval for Off-Policy Evaluation and Policy Optimization

Weaknesses: The study of bias issue is important, but I am not fully convinced the motivation of this so-called "confidence interval". Normally the confidence interval is designed for uncertain quantification and thus of great practical interest. However, although the authors explicitly point out they do not consider uncertainties, this will rule out all the important applications that typical CI could do (safe RL or else) (this CI will not be valid in practice due to estimation error). Thus, I can only view the contribution in this paper as sort of additional guarantee for the algorithm proposed in "Minimax Weight and Q-Function Learning for Off-Policy Evaluation" since the algorithms are the same. Solely quantifying a bias of an existing estimator may not be viewed as sufficiently significant.