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Updated: Sep 12, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
COVARIANCE LOSS, SZEMEREDI REGULARITY, AND DIFFERENTIAL PRIVACY
March Boedihardjo1, Thomas Strohmer2, Roman Vershynin3
1Department of Mathematics, Michigan State University, East Lansing, USA.
Abstract:
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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