Review for NeurIPS paper: Kernel Alignment Risk Estimator: Risk Prediction from Training Data

Weaknesses: I have read the rebuttal and other reviewers' comments. The rebuttal addressed my questions and thus I increased the score to 7. Nevertheless, I suggest the authors carefully organize the paper for clarity in the final version. The quality of this paper is good, but there are some issues that I concerned: Motivation and related works - The Gaussianity assumption: This paper considers the gaussian data, that follows with previous works in RMT, e.g., [17,20]. Also the following refs forcuses on the risk convergence of (centered) KRR by RMT in an asymptotic regime. It's ok, but in this case, the motivation in the introduction should be better presented when compared to current results in RMT.