Review for NeurIPS paper: Learning Robust Decision Policies from Observational Data

Weaknesses: There are many algorithmic points that I did not find addressed in this submission and would give supplemental insight, in addition to the application of the conformal prediction result. I appreciated the guarantee that the confidence interval is valid. However, is there any room to discuss optimality (an equivalent of power for hypothesis testing?)? When would such a method break and produce a useless interval? What is the price (in terms of "power") of using as predictor the locally weighted average of cost in Eq. (11)?