Four algorithms for the the efficient computation of truncated pivoted QR approximations to a sparse matrix |
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Authors: | GW Stewart |
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Institution: | (1) Department of Computer Science and Institute for Advanced Computer Studies, University of Maryland, College Park, MD 20742, USA , US |
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Abstract: | Summary. In this paper we propose four algorithms to compute truncated pivoted QR approximations to a sparse matrix. Three are based
on the Gram–Schmidt algorithm and the other on Householder triangularization. All four 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.
Received February 23, 1998 / Revised version received April 16, 1998 |
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Keywords: | Mathematics Subject Classification (1991):65F20 65F50 |
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