List questions from hessian-matrix

Published on 10 Sep 2019 - 8:51

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Hessian matrix in cylindrical coordinate basis

Published on 11 Sep 2019 - 14:50

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Proving complicated convexity example

Published on 16 Sep 2019 - 13:26

120

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Generic expression for Hessian

Published on 20 Sep 2019 - 7:59

798

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Finding the gradient and Hessian of $\frac{1}{2}|Ax-By|^2$

Published on 22 Sep 2019 - 21:00

65

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Show that if $g(x)=f(Ax)$, then $H_x(g)=A^tH_{Ax}(f)A$ , where $H$ means the hessian matrix

Published on 23 Sep 2019 - 23:05

47

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For which values of $a\in \mathbb{R}$ is there a max or min for $f(x,y) = (x-1)^2 +2a(x-1)y +y^2 +y^4$ in $(1,0)$?

Published on 24 Sep 2019 - 14:54

69

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Since Hessians are symmetric, it holds that Hessians have all real eigenvalues

Published on 26 Sep 2019 - 13:43

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Informative proof that any real-valued symmetric matrix only has real eigenvalues

Published on 26 Sep 2019 - 17:03

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$f$ is convex function iff Hessian matrix is nonnegative-definite.

Published on 20 Mar 2014 - 19:43

999

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Hessian of a quadratic function

Published on 25 Mar 2026 - 4:37

574

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Show that $f(x)=\log(e^{x_1}+...+e^{x_n})$ is convex

Published on 18 Sep 2014 - 3:27

316

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The relation between the largest eigenvalue of $f's$ Hessian matrix and Lipschitz constant of the gradient of $f$

Published on 06 Oct 2019 - 13:15

98

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Gradient of $\frac{<Ax,x>}{|x|^2}$

Published on 06 Oct 2019 - 21:34

92

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What is the Hessian matrix of the following expression?

Published on 25 Mar 2026 - 11:16

List Question

Under what conditions $J^{T}J$ equals to the Hessian?

Hessian matrix in cylindrical coordinate basis

Proving complicated convexity example

Generic expression for Hessian

Finding the gradient and Hessian of $\frac{1}{2}|Ax-By|^2$

Show that if $g(x)=f(Ax)$, then $H_x(g)=A^tH_{Ax}(f)A$ , where $H$ means the hessian matrix

For which values of $a\in \mathbb{R}$ is there a max or min for $f(x,y) = (x-1)^2 +2a(x-1)y +y^2 +y^4$ in $(1,0)$?

Since Hessians are symmetric, it holds that Hessians have all real eigenvalues

Informative proof that any real-valued symmetric matrix only has real eigenvalues

$f$ is convex function iff Hessian matrix is nonnegative-definite.

Hessian of a quadratic function

Show that $f(x)=\log(e^{x_1}+...+e^{x_n})$ is convex

The relation between the largest eigenvalue of $f's$ Hessian matrix and Lipschitz constant of the gradient of $f$

Gradient of $\frac{<Ax,x>}{|x|^2}$

What is the Hessian matrix of the following expression?

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