Randomized Algorithms for Low-Rank Matrix Factorizations: Sharp Performance Bounds
The development of randomized algorithms for numerical linear algebra, e.g. for computing approximate QR and SVD factorizations, has recently become an intense area of research. This paper studies one of the most frequently discussed algorithms in the literature for dimensionality reduction—specific...
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| Published in: | Algorithmica Vol. 72; no. 1; pp. 264 - 281 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Boston
Springer US
01.05.2015
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| Subjects: | |
| ISSN: | 0178-4617, 1432-0541 |
| Online Access: | Get full text |
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