Algorithm 805: computation and uses of the semidiscrete matrix decomposition
Title | Algorithm 805: computation and uses of the semidiscrete matrix decomposition |
Publication Type | Journal Articles |
Year of Publication | 2000 |
Authors | Kolda TG, O'Leary DP |
Journal | ACM Trans. Math. Softw. |
Volume | 26 |
Issue | 3 |
Pagination | 415 - 435 |
Date Published | 2000/09// |
ISBN Number | 0098-3500 |
Keywords | compression, latent semantic indexing, Matrix decomposition, semidiscrete decompositin, singular value decomposition |
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. |
URL | http://doi.acm.org/10.1145/358407.358424 |
DOI | 10.1145/358407.358424 |