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Algorithm 805: computation and uses of the semidiscrete matrix decomposition

Authors:

Tamara G. Kolda,

Dianne P. O'LearyAuthors Info & Claims

ACM Transactions on Mathematical Software (TOMS), Volume 26, Issue 3

Pages 415 - 435

https://doi.org/10.1145/358407.358424

Published: 01 September 2000 Publication History

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Abstract

We present algorithms for computing a semidiscrete approximation to a matrix in a weighted norm, with the Frobenius norm as a special case. The approximation is formed as a weighted sum of outer products of vectors whose elements are ±1 or 0, so the storage required by the approximation is quite small. We also present a related algorithm for approximation of a tensor. Applications of the algorithms are presented to data compression, filtering, and information retrieval; software is provided in C and in Matlab.

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References

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Published In

ACM Transactions on Mathematical Software Volume 26, Issue 3

Sept. 2000

139 pages

ISSN:0098-3500

EISSN:1557-7295

DOI:10.1145/358407

Editor:
Ronald F. Boisvert
National Institute of Standards and Technology, Gaithersburg, MD

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Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 01 September 2000

Published in TOMS Volume 26, Issue 3

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