Deterministic graph spectral sparsification

Abstract

An important technique in data analysis is principal component analysis or PCA. Given a covariance matrix S, in PCA we need to compute the eigenvector associated to a greatest eigenvalue of S in order to determine the direction of the so-called principal components.