Thomas Lumley • 2/5/2016

Stochastic SVD

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This technical article details the Stochastic Singular Value Decomposition (SVD) algorithm. It explains how random projection matrices can be used to efficiently approximate the range and dominant singular values of a large matrix, enabling faster computations than traditional methods. It covers the theory, practical benefits like easier implementation and parallelization, and references the foundational paper by Halko, Martinsson, and Tropp.

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#linear algebra #Numerical Methods #Svd
Stochastic SVD

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