Question

Approximate matrix by a rank 2 matrix using singular values

score 11k · Answer 1 · 2014-12-14 20:28:23

11k

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Approximate matrix by a rank 2 matrix using singular values

Published on 14 Dec 2014 - 20:28

score 2.7k · Answer 2 · 2014-12-14 23:18:32

2.7k

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Can a matrix have more than one inverse (Singular Value Decomposition)

Published on 14 Dec 2014 - 23:18

score 62 · Answer 3 · 2014-12-18 07:53:34

62

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Replacing Singular Values of a Matrix with Complex Ones

Published on 18 Dec 2014 - 7:53

score 72 · Answer 4 · 2014-12-19 11:45:32

72

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If A and A' are approximately the same, are their principal components/SVD very close?

Published on 19 Dec 2014 - 11:45

score 344 · Answer 5 · 2014-12-20 23:21:04

344

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Why the largest singular value of a magic matrix is its magic constant?

Published on 20 Dec 2014 - 23:21

score 1.2k · Answer 6 · 2014-12-26 01:09:15

1.2k

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If we have SVD of a submatrix, is that useful for SVD of full matrix?

Published on 26 Dec 2014 - 1:09

score 7.6k · Answer 7 · 2026-03-25 13:49:38

7.6k

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Tikhonov regularization vs truncated SVD

Published on 25 Mar 2026 - 13:49

score 104 · Answer 8 · 2014-12-29 17:46:25

104

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Does the following type of "SVD" exist?

Published on 29 Dec 2014 - 17:46

score 460 · Answer 9 · 2026-03-22 19:33:56

460

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uniqueness of svd decomposition and its role in statistical analysis

Published on 22 Mar 2026 - 19:33

score 2.1k · Answer 10 · 2026-03-26 13:30:22

2.1k

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Restrictions to simplify computation of matrix powers with SVD

Published on 26 Mar 2026 - 13:30

score 226 · Answer 11 · 2019-10-04 19:51:21

226

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Angle between the singular vectors of a matrix A and the singular vectors of Transpose(A)

Published on 04 Oct 2019 - 19:51

score 237 · Answer 12 · 2019-10-05 00:02:16

237

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Given $W=ULV^T$ and a vector $\mathbf{x}$, can we compute $UL^kV^T\mathbf{x}$ without doing the SVD, for any integer k?

Published on 05 Oct 2019 - 0:02

score 54 · Answer 13 · 2026-03-25 12:33:52

54

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Describe in a sentence to perform Singular Value Decomposition (SVD) for all $t$.

Published on 25 Mar 2026 - 12:33

score 649 · Answer 14 · 2019-10-06 18:07:49

649

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Trace of SVD low rank in Frobenius norm

Published on 06 Oct 2019 - 18:07

score 89 · Answer 15 · 2019-10-10 11:24:56

89

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Is the orthogonal polar factor of matrices of nullity 1 smooth?

Published on 10 Oct 2019 - 11:24

List Question

Approximate matrix by a rank 2 matrix using singular values

Can a matrix have more than one inverse (Singular Value Decomposition)

Replacing Singular Values of a Matrix with Complex Ones

If A and A' are approximately the same, are their principal components/SVD very close?

Why the largest singular value of a magic matrix is its magic constant?

If we have SVD of a submatrix, is that useful for SVD of full matrix?

Tikhonov regularization vs truncated SVD

Does the following type of "SVD" exist?

uniqueness of svd decomposition and its role in statistical analysis

Restrictions to simplify computation of matrix powers with SVD

Angle between the singular vectors of a matrix A and the singular vectors of Transpose(A)

Given $W=ULV^T$ and a vector $\mathbf{x}$, can we compute $UL^kV^T\mathbf{x}$ without doing the SVD, for any integer k?

Describe in a sentence to perform Singular Value Decomposition (SVD) for all $t$.

Trace of SVD low rank in Frobenius norm

Is the orthogonal polar factor of matrices of nullity 1 smooth?

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