  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.
