Question

Comparing SVD of orthogonal matrix $(\sqrt{W}A)$ and matrix $A$ in order to find the singular values of A

score 359 · Answer 1 · 2018-09-11 23:16:02

359

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Comparing SVD of orthogonal matrix $(\sqrt{W}A)$ and matrix $A$ in order to find the singular values of A

Published on 11 Sep 2018 - 23:16

score 654 · Answer 2 · 2018-09-12 20:14:42

654

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Eckart–Young–Mirsky theorem: rank $\le$ k or rank = k

Published on 12 Sep 2018 - 20:14

score 237 · Answer 3 · 2018-09-18 14:00:48

237

Views

Low rank approximation of non-symmetrix square matrix

Published on 18 Sep 2018 - 14:00

score 87 · Answer 4 · 2026-03-25 02:57:35

87

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Kronecker product SVD Error bound

Published on 25 Mar 2026 - 2:57

score 2.3k · Answer 5 · 2018-09-23 18:56:43

2.3k

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Does SVD give the best rank 1 approximation with respect to the Frobenius norm, L2 norm, or both?

Published on 23 Sep 2018 - 18:56

score 74 · Answer 6 · 2018-10-01 16:44:15

74

Views

U matrix in Singular value decompositon.

Published on 01 Oct 2018 - 16:44

score 52 · Answer 7 · 2018-10-05 09:59:09

52

Views

Using SVD to express the normalized norm of the output of a linear map

Published on 05 Oct 2018 - 9:59

score 50 · Answer 8 · 2018-10-08 20:23:52

50

Views

Condition for product of tow rectangular matirx is diagonalizable?

Published on 08 Oct 2018 - 20:23

score 79 · Answer 9 · 2018-10-10 20:17:10

79

Views

Column Orderings in any QR/Matrix Factorization Method

Published on 10 Oct 2018 - 20:17

score 126 · Answer 10 · 2018-10-11 14:14:24

126

Views

Residual error of a normalized DLT

Published on 11 Oct 2018 - 14:14

score 919 · Answer 11 · 2026-03-23 11:52:23

919

Views

Prove that rank(A) = rank(A$^\dagger$)=rank(AA$^\dagger$)=rank(A$^\dagger$A) using the SVD decomposition

Published on 23 Mar 2026 - 11:52

score 18.9k · Answer 12 · 2026-03-16 23:07:23

18.9k

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Finding the best rank-one approximation of the matrix $\bf A$

Published on 16 Mar 2026 - 23:07

score 676 · Answer 13 · 2018-10-23 10:00:54

676

Views

Why eigenvectors of $\mathbf{A}^T\mathbf{A}$ are in row space of $\mathbf{A}$?

Published on 23 Oct 2018 - 10:00

score 226 · Answer 14 · 2018-10-24 22:25:00

226

Views

Relationships between top-$k$ eigenvector and top-$k$ singular vector of symmetric matrix $A$

Published on 24 Oct 2018 - 22:25

score 105 · Answer 15 · 2026-03-25 03:01:07

105

Views

can we perform SVD in spectral clustering to get top-$k$ eigenvector?

Published on 25 Mar 2026 - 3:01

List Question

Comparing SVD of orthogonal matrix $(\sqrt{W}A)$ and matrix $A$ in order to find the singular values of A

Eckart–Young–Mirsky theorem: rank $\le$ k or rank = k

Low rank approximation of non-symmetrix square matrix

Kronecker product SVD Error bound

Does SVD give the best rank 1 approximation with respect to the Frobenius norm, L2 norm, or both?

U matrix in Singular value decompositon.

Using SVD to express the normalized norm of the output of a linear map

Condition for product of tow rectangular matirx is diagonalizable?

Column Orderings in any QR/Matrix Factorization Method

Residual error of a normalized DLT

Prove that rank(A) = rank(A$^\dagger$)=rank(AA$^\dagger$)=rank(A$^\dagger$A) using the SVD decomposition

Finding the best rank-one approximation of the matrix $\bf A$

Why eigenvectors of $\mathbf{A}^T\mathbf{A}$ are in row space of $\mathbf{A}$?

Relationships between top-$k$ eigenvector and top-$k$ singular vector of symmetric matrix $A$

can we perform SVD in spectral clustering to get top-$k$ eigenvector?

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