Restarted Lanczos Bidiagonalization for the SVD in SLEPc
نویسندگان
چکیده
منابع مشابه
A Robust and Efficient Parallel SVD Solver Based on Restarted Lanczos Bidiagonalization
Lanczos bidiagonalization is a competitive method for computing a partial singular value decomposition of a large sparse matrix, that is, when only a subset of the singular values and corresponding singular vectors are required. However, a straightforward implementation of the algorithm has the problem of loss of orthogonality between computed Lanczos vectors, and some reorthogonalization techn...
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New restarted Lanczos bidiagonalization methods for the computation of a few of the largest or smallest singular values of a large matrix are presented. Restarting is carried out by augmentation of Krylov subspaces that arise naturally in the standard Lanczos bidiagonalization method. The augmenting vectors are associated with certain Ritz or harmonic Ritz vectors. Computed examples show the ne...
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The irlba package provides a fast way to compute partial singular value decompositions (SVD) of large sparse or dense matrices. Recent additions to the package can also compute fast partial symmetric eigenvalue decompositions and principal components. The package is an R implementation of the augmented implicitly restarted Lanczos bidiagonalization algorithm of Jim Baglama and Lothar Reichel. S...
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تاریخ انتشار 2015