Question

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

score 363 · Answer 1 · 2026-05-10 14:49:20

363

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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 10 May 2026 - 14:49

score 657 · Answer 2 · 2026-04-16 18:51:53

657

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

Published on 16 Apr 2026 - 18:51

score 240 · Answer 3 · 2026-04-15 13:07:48

240

Views

Low rank approximation of non-symmetrix square matrix

Published on 15 Apr 2026 - 13:07

score 92 · Answer 4 · 2026-05-10 17:58:16

92

Views

Kronecker product SVD Error bound

Published on 10 May 2026 - 17:58

score 2.3k · Answer 5 · 2026-04-17 01:20:55

2.3k

Views

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

Published on 17 Apr 2026 - 1:20

score 77 · Answer 6 · 2026-04-12 07:41:42

77

Views

U matrix in Singular value decompositon.

Published on 12 Apr 2026 - 7:41

score 55 · Answer 7 · 2026-04-11 16:58:11

55

Views

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

Published on 11 Apr 2026 - 16:58

score 53 · Answer 8 · 2026-04-13 15:01:39

53

Views

Condition for product of tow rectangular matirx is diagonalizable?

Published on 13 Apr 2026 - 15:01

score 82 · Answer 9 · 2026-04-09 05:17:39

82

Views

Column Orderings in any QR/Matrix Factorization Method

Published on 09 Apr 2026 - 5:17

score 129 · Answer 10 · 2026-04-13 00:48:34

129

Views

Residual error of a normalized DLT

Published on 13 Apr 2026 - 0:48

score 920 · Answer 11 · 2026-03-25 11:13:31

920

Views

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

Published on 25 Mar 2026 - 11:13

score 18.9k · Answer 12 · 2026-04-29 12:42:22

18.9k

Views

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

Published on 29 Apr 2026 - 12:42

score 679 · Answer 13 · 2026-04-13 22:48:54

679

Views

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

Published on 13 Apr 2026 - 22:48

score 229 · Answer 14 · 2026-04-13 02:39:38

229

Views

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

Published on 13 Apr 2026 - 2:39

score 110 · Answer 15 · 2026-05-10 14:05:51

110

Views

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

Published on 10 May 2026 - 14:05

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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