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Low-rank incremental methods for computing dominant singular subspaces

✍ Scribed by C.G. Baker; K.A. Gallivan; P. Van Dooren


Book ID
113772042
Publisher
Elsevier Science
Year
2012
Tongue
English
Weight
782 KB
Volume
436
Category
Article
ISSN
0024-3795

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## Abstract Many applications, such as subspace‐based models in information retrieval and signal processing, require the computation of singular subspaces associated with the __k__ dominant, or largest, singular values of an __m__Γ—__n__ data matrix __A__, where __k__β‰ͺmin(__m__,__n__). Frequently, _