Two Algorithms for the The Efficient Computation of Truncated Pivoted QR Approximations to a Sparse Matrix

TitleTwo Algorithms for the The Efficient Computation of Truncated Pivoted QR Approximations to a Sparse Matrix
Publication TypeReports
Year of Publication1998
AuthorsStewart G.W
Date Published1998/10/15/
InstitutionInstititue for Advanced Computer Studies, Univ of Maryland, College Park
KeywordsTechnical Report
Abstract

In this note we propose two algorithms to compute truncated pivoted QRapproximations to a sparse matrix. One is based on the Gram--Schmidt
algorithm, and the other on Householder triangularization. Both
algorithms leave the original matrix unchanged, and the only
additional storage requirements are arrays to contain the
factorization itself. Thus, the algorithms are particularly suited to
determining low-rank approximations to a sparse matrix.
(Also cross-referenced as UMIACS-TR-98-12)
URLhttp://drum.lib.umd.edu/handle/1903/941