Publication
Allerton 2013
Conference paper

Robust subspace iteration and privacy-preserving spectral analysis

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Abstract

We discuss a new robust convergence analysis of the well-known subspace iteration algorithm for computing the dominant singular vectors of a matrix, also known as simultaneous iteration or power method. The result characterizes the convergence behavior of the algorithm when a large amount noise is introduced after each matrix-vector multiplication. While interesting in its own right, the main motivation comes from the problem of privacy-preserving spectral analysis where noise is added in order to achieve the privacy guarantee known as differential privacy. © 2013 IEEE.

Date

02 Oct 2013

Publication

Allerton 2013

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