Question

Deriving Singular Value Decompositionusing diagonalizability

score 20 · Answer 1 · 2015-11-10 03:02:33

20

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Deriving Singular Value Decompositionusing diagonalizability

Published on 10 Nov 2015 - 3:02

score 3.9k · Answer 2 · 2026-03-10 10:53:08

3.9k

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Largest eigenvector as the rank-1 approximation

Published on 10 Mar 2026 - 10:53

score 768 · Answer 3 · 2026-03-26 00:56:29

768

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Solve the problem $Ax = 0$ when $A$ has full rank.

Published on 26 Mar 2026 - 0:56

score 732 · Answer 4 · 2015-11-17 12:01:54

732

Views

SVD of concatenate matrices

Published on 17 Nov 2015 - 12:01

score 45 · Answer 5 · 2015-11-18 14:44:12

45

Views

Why do the singular vectors $u_i$ and $v_i$ become oscillatory as $\sigma_i$ decreases?

Published on 18 Nov 2015 - 14:44

score 6k · Answer 6 · 2026-03-11 21:01:43

6k

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What forms does the Moore-Penrose inverse take under systems with full rank, full column rank, and full row rank?

Published on 11 Mar 2026 - 21:01

score 5.2k · Answer 7 · 2015-11-22 23:56:35

5.2k

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What is the best way to compute the pseudoinverse of a matrix?

Published on 22 Nov 2015 - 23:56

score 47 · Answer 8 · 2015-11-26 16:42:36

47

Views

Tracking Matrix Decomposition after row subset selection

Published on 26 Nov 2015 - 16:42

score 4.5k · Answer 9 · 2015-11-28 19:02:08

4.5k

Views

Pseudo inverse of a singular value decomposition SVD is equal to its "real" inverse for a square matrix?

Published on 28 Nov 2015 - 19:02

score 8.6k · Answer 10 · 2015-11-29 12:18:20

8.6k

Views

Proof of "Singular values of a normal matrix are the absolute values of its eigenvalues"

Published on 29 Nov 2015 - 12:18

score 243 · Answer 11 · 2026-03-28 04:29:08

243

Views

Why is $S$ in SVD a vector instead of a matrix?

Published on 28 Mar 2026 - 4:29

score 1.3k · Answer 12 · 2015-12-15 00:26:57

1.3k

Views

Image of unit sphere being hyper ellipse proof (SVD)

Published on 15 Dec 2015 - 0:26

score 223 · Answer 13 · 2015-12-15 19:07:59

223

Views

Modifying the result matrices of SVD so that $\Sigma$ is canonical form

Published on 15 Dec 2015 - 19:07

score 479 · Answer 14 · 2015-12-18 02:45:20

479

Views

How to get the SVD of $2AA^T-\operatorname{diag}(AA^T)$ given $A$ and its SVD $A=USV^T$?

Published on 18 Dec 2015 - 2:45

score 764 · Answer 15 · 2015-12-29 17:05:21

764

Views

What does the orthogonalisation step for U and V in SVD do exactly?

Published on 29 Dec 2015 - 17:05

List Question

Deriving Singular Value Decompositionusing diagonalizability

Largest eigenvector as the rank-1 approximation

Solve the problem $Ax = 0$ when $A$ has full rank.

SVD of concatenate matrices

Why do the singular vectors $u_i$ and $v_i$ become oscillatory as $\sigma_i$ decreases?

What forms does the Moore-Penrose inverse take under systems with full rank, full column rank, and full row rank?

What is the best way to compute the pseudoinverse of a matrix?

Tracking Matrix Decomposition after row subset selection

Pseudo inverse of a singular value decomposition SVD is equal to its "real" inverse for a square matrix?

Proof of "Singular values of a normal matrix are the absolute values of its eigenvalues"

Why is $S$ in SVD a vector instead of a matrix?

Image of unit sphere being hyper ellipse proof (SVD)

Modifying the result matrices of SVD so that $\Sigma$ is canonical form

How to get the SVD of $2AA^T-\operatorname{diag}(AA^T)$ given $A$ and its SVD $A=USV^T$?

What does the orthogonalisation step for U and V in SVD do exactly?

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