Review for NeurIPS paper: Differentially Private Clustering: Tight Approximation Ratios

Additional Feedback: I think this is a very well written manuscript. Some low-level/stylistic comments: -I think a more detailed statement of the last known bound from NS18 (approximation ratio, additive error, and running time) might have been useful for the reader. I found this a bit misleading for someone who does not know what k-means/median is (ell_2 is not just the square of ell_1 beyond the real line). So I would remove "without privacy constraints" from this sentence. I consider learning with a margin to be on separable data, that is, realizable, by default.