List questions from positive-semidefinite

Published on 10 May 2017 - 15:13

258

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Expected eigenvalues of Gram matrix

Published on 11 May 2017 - 2:32

200

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Maximum bound of Contraction Matrix

Published on 11 May 2017 - 9:46

68

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To Show This Is Positive Semidefinite

Published on 12 May 2017 - 6:14

2.5k

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Definiteness of a general partitioned matrix $\mathbf M=\left[\begin{matrix}\bf A & \bf B\\\bf B^\top & \bf D \\\end{matrix}\right]$

Published on 14 May 2017 - 15:37

29

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Cholsky and Group Structure of Correlation matrices

Published on 17 May 2017 - 16:46

313

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Difficulty in linear algebra question.

Published on 20 May 2017 - 6:04

1k

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What does it mean for the Hessian of a convex function to be positive semidefinite?

Published on 22 May 2017 - 7:02

147

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Simple sufficient conditions for matrix positive semidefiniteness?

Published on 26 May 2017 - 21:16

82

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If $A$ and $B$ are respectively positive-definite and positive-semidefinite matrices, is $A^T B A - B \ge 0$?

Published on 28 May 2017 - 11:32

1.1k

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Checking the convexity of an optimization problem using the Hessian

Published on 31 May 2017 - 10:26

424

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About trace of product of unitary and symmetric positive semidefinite matrices

Published on 04 Jun 2017 - 22:59

244

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Necessary & sufficient condition for this matrix to be positive semi-definite?

Published on 09 Jun 2017 - 23:28

1.8k

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If a matrix $A$, not necessarily symmetric, has real, nonnegative eigenvalues, is it positive semidefinite?

Published on 13 Jun 2017 - 21:45

97

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$\sum_i x_i^2 +\sum_i\sum_{i\neq j}B_{ij}x_i x_j \geq 0$?

Published on 15 Jun 2017 - 18:28

List Question

Relationship between highest eigenvalue and rank of PSD matrix

Expected eigenvalues of Gram matrix

Maximum bound of Contraction Matrix

To Show This Is Positive Semidefinite

Definiteness of a general partitioned matrix $\mathbf M=\left[\begin{matrix}\bf A & \bf B\\\bf B^\top & \bf D \\\end{matrix}\right]$

Cholsky and Group Structure of Correlation matrices

Difficulty in linear algebra question.

What does it mean for the Hessian of a convex function to be positive semidefinite?

Simple sufficient conditions for matrix positive semidefiniteness?

If $A$ and $B$ are respectively positive-definite and positive-semidefinite matrices, is $A^T B A - B \ge 0$?

Checking the convexity of an optimization problem using the Hessian

About trace of product of unitary and symmetric positive semidefinite matrices

Necessary & sufficient condition for this matrix to be positive semi-definite?

If a matrix $A$, not necessarily symmetric, has real, nonnegative eigenvalues, is it positive semidefinite?

$\sum_i x_i^2 +\sum_i\sum_{i\neq j}B_{ij}x_i x_j \geq 0$?

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