Covariance loss, Szemeredi regularity, and differential privacy

01/06/2023
by   March Boedihardjo, et al.
0

We show how randomized rounding based on Grothendieck's identity can be used to prove a nearly tight bound on the covariance loss–the amount of covariance that is lost by taking conditional expectation. This result yields a new type of weak Szemeredi regularity lemma for positive semidefinite matrices and kernels. Moreover, it can be used to construct differentially private synthetic data.

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