Review for NeurIPS paper: Learning Kernel Tests Without Data Splitting

Additional Feedback: Minor comments ******************* - l.55 the observed test statistic \hat{\tau} is never really defined, in particular w.r.t. This might be a bit confusing - I think Lemma 1 needs rephrasing. In particular, by definition the expectation of \tau is already that of h, so one does not need to assume anything here. And the variance of \tau is \sigma 2 / n. Since \tau is already defined in the previous paragraph, writing "Let \mu denote E[h] and \sigma 2 Var(h)" seems enough - missing \mid H_A in eq 1? - l. 137 the e_j vectors are not defined, although it remains understandable.