Review for NeurIPS paper: On Convergence of Nearest Neighbor Classifiers over Feature Transformations

Summary and Contributions: Update: Thanks for addressing the concerns raised by the reviewers, based on re-reading the paper and going over the comments, I am able to understand the experiments better - and based on the authors comments that they will revise the draft to make things more clear, I will change my score to accept. Having said that, I would still keep my confidence low since I am unable to accurately access the significance of the result and I believe that would be a key factor to consider in a novel theoretical paper. The result is based on two key properties of the transformed space that they identify. The first is'safety', which is a measure of how well can we recover the posterior in the original space from the feature space. The second is smoothness, which is a measure of how hard it is to recover the posterior in the original space from the feature space.