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- W3100283647 abstract "This paper describes a suite of algorithms for constructing low-rank approximations of an input matrix from a random linear image of the matrix, called a sketch. These methods can preserve structural properties of the input matrix, such as positive-semidefiniteness, and they can produce approximations with a user-specified rank. The algorithms are simple, accurate, numerically stable, and provably correct. Moreover, each method is accompanied by an informative error bound that allows users to select parameters a priori to achieve a given approximation quality. These claims are supported by numerical experiments with real and synthetic data." @default.
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- W3100283647 date "2017-01-01" @default.
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- W3100283647 title "Practical Sketching Algorithms for Low-Rank Matrix Approximation" @default.
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- W3100283647 doi "https://doi.org/10.1137/17m1111590" @default.
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