Gap-free Differentially Private PCA for Gaussian Data

Privacy-Preserving Technologies in DataSparse and Compressive Sensing TechniquesStochastic Gradient Optimization TechniquesPrincipal component analysisGaussianPattern recognition (psychology)+2

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Abstract

We give a gap-free differentially private algorithm for the principal component analysis (PCA) problem with Gaussian data.

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