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I am looking for a source (book, online book, etc..) where I can find the theory behind low-rank approximations of matrices. In particular, I am interested in low-rank approximations used in optimization problems, such as minimizations of the Euclidean and Forbenius norms.

I have some background in basic and numberical linear algebra, but I am looking for a source that is simple and straightforward.

Sincerly, Amit.

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up vote 2 down vote accepted

The book Low Rank Approximation: Algorithms, Implementation, Applications by Ivan Markovsky might be of intrest here. The table of content is available in the Amazon link.

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