List questions from svd

Published on 01 Nov 2014 - 22:26

1.3k

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Is the product eigenvalues less than or equal to the product of singular values?

Published on 11 Nov 2014 - 11:14

799

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What does it mean by one matrix is unitarily similar to another?

Published on 13 Nov 2014 - 15:42

1.3k

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Singular Value Decomposition in Axler's book

Published on 15 Nov 2014 - 17:44

3.6k

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Row space and column space for SVD

Published on 17 Nov 2014 - 9:09

260

Views

Analytical solution to the first PCA direction

Published on 25 Nov 2014 - 11:34

88

Views

principal eigenvectors of an unknown matrix

Published on 25 Nov 2014 - 16:39

768

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Incorrect angle detected between two planes

Published on 28 Nov 2014 - 6:04

4.5k

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Best fitting circle to points in 3D

Published on 28 Nov 2014 - 12:36

2k

Views

Why can SVD handle rank-deficient matrices?

Published on 03 Dec 2014 - 11:52

734

Views

Why are singular values of a positive

Published on 08 Dec 2014 - 21:22

2.4k

Views

The less than full rank case, can be done with SVD decomposition?

Published on 08 Dec 2014 - 23:45

108

Views

Algorithm to efficiently compute$ A^k$

Published on 09 Dec 2014 - 6:46

1.2k

Views

Left singular vectors of an orthogonal matrix $X$ are the same as the right singular vectors of $X^T$

Published on 10 Dec 2014 - 18:00

241

Views

SVD, ALSWR tutorial

Published on 11 Dec 2014 - 20:42

List Question

Connection between results of two SVDs

Is the product eigenvalues less than or equal to the product of singular values?

What does it mean by one matrix is unitarily similar to another?

Singular Value Decomposition in Axler's book

Row space and column space for SVD

Analytical solution to the first PCA direction

principal eigenvectors of an unknown matrix

Incorrect angle detected between two planes

Best fitting circle to points in 3D

Why can SVD handle rank-deficient matrices?

Why are singular values of a positive

The less than full rank case, can be done with SVD decomposition?

Algorithm to efficiently compute$ A^k$

Left singular vectors of an orthogonal matrix $X$ are the same as the right singular vectors of $X^T$

SVD, ALSWR tutorial

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