NeurIPS 2020

Private Identity Testing for High-Dimensional Distributions

Meta Review

This paper studies the problem of privately answering if a dataset comes from the uniform distribution (or "far away"). The paper provides improved sample complexity and show tightness of the sample complexity (information theoeretically). Overall the result is novel and interesting. Please note reviewer's comments on clarity and improve the presentation.