A Jacobi-Davidson type SVD method

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    We discuss a new method for the iterative computation of a portion of the singular values and vectors of a large sparse matrix. Similar to the Jacobi--Davidson method for the eigenvalue problem, we compute in each step a correction by (approximately) solving a correction equation. We give a few variants of this Jacobi--Davidson SVD (JDSVD) method with their theoretical properties. It is shown that the JDSVD can be seen as an accelerated (inexact) Newton scheme. We experimentally compare the method with some other iterative SVD methods
    Original languageEnglish
    Pages (from-to)606-628
    JournalSIAM Journal on Scientific Computing
    Issue number2
    Publication statusPublished - 2001


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