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- W2024281837 abstract "Low rank approximation of large and/or sparse rectangular matrices is a very import ant topic in many application problems and is closely related to the sin- gular value decomposition of the matrices. In this paper, we propose an implicit restart scheme for the bidiagonal Lanczos algorithm to compute a subset of the dominating singular triplets. We also illustrate the connection of the method with inverse eigenvalue problems. In the Lanczos process, we use the so-called one-sided reorthogonalization strategy to maintain the orthogonality level of the Lanczos vec- tors. The efficiency and the applicability of our algorithm are illustrated by some numerical examples from information retrieval applications." @default.
- W2024281837 created "2016-06-24" @default.
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- W2024281837 date "1998-08-01" @default.
- W2024281837 modified "2023-09-25" @default.
- W2024281837 title "An implicitly restarted bidiagonal Lanczos Method forLarge-scale singular value problems" @default.
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- W2024281837 doi "https://doi.org/10.2172/6451" @default.
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