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• W3167912251 abstract "In this paper, we describe a new algorithm to compute the extreme eigenvalue/eigenvector pairs of a symmetric matrix. The proposed algorithm can be viewed as an extension of the Jacobi transformation method for symmetric matrix diagonalization to the case where we want to compute just a few eigenvalues/eigenvectors. The method is also particularly well suited for the computation of sparse eigenspaces. We show the effectiveness of the method for sparse low-rank approximations and show applications to random symmetric matrices, graph Fourier transforms, and with the sparse principal component analysis in image classification experiments." @default.
• W3167912251 created "2021-06-22" @default.
• W3167912251 creator A5075074301 @default.
• W3167912251 date "2021-05-30" @default.
• W3167912251 modified "2023-09-27" @default.
• W3167912251 title "An iterative Jacobi-like algorithm to compute a few sparse eigenvalue-eigenvector pairs." @default.
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• W3167912251 hasPublicationYear "2021" @default.
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