List questions from hessian-matrix

Published on 31 Dec 2017 - 17:58

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Determining Strictly Concave/Convex Function

Published on 02 Jan 2018 - 1:02

8.6k

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Are there any Hessian matrices that are asymmetric on a large set?

Published on 28 Mar 2011 - 15:58

7k

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Geometric interpretation of $\frac {\partial^2} {\partial x \partial y} f(x,y)$

Published on 27 Mar 2026 - 22:10

1.3k

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A quick question about the Hessian matrix

Published on 19 Mar 2012 - 18:11

24.6k

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Hessian matrix of a quadratic form

Published on 17 Nov 2012 - 13:18

3.4k

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Second order approximation of $\log \det X$

Published on 26 Mar 2026 - 2:34

218

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Hessian of restriction of a map to the boundary of a domain

Published on 05 Aug 2020 - 1:04

47

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Potential function with a fixed set of minima and no poles.

Published on 12 Aug 2020 - 6:20

1.1k

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Where Does the Hessian Matrix Come from (Why Does it Work)?

Published on 12 Aug 2020 - 11:59

326

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Hessian for Matrix Factorization objective

Published on 13 Aug 2020 - 6:05

622

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Does the positive semidefiniteness of a function not necessarily imply the function is convex?

Published on 29 Mar 2026 - 13:23

794

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Computing the diagonal approximation of the Hessian of the Pearson Correlation

Published on 24 Aug 2020 - 11:50

97

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Show $f(x) = \frac{1}{2} x_1^2 + \frac{1}{2} x_2^2 - \log(1 + x_1 + x_2)$ is strongly convex and find its parameter.

Published on 25 Aug 2020 - 1:34

127

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If $f$ is twice differentiable at $a$, prove $f''(a) vw= \lim_{k \rightarrow \infty} \frac{f(a+t_k(v_k+w_k))-f(a+t_kv_k)-f(a+t_kw_k)+f(a)}{t_k^2}$

Published on 25 Aug 2020 - 23:24

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Matrix calculus: Second-order derivative matrix using chain rule

Determining Strictly Concave/Convex Function

Are there any Hessian matrices that are asymmetric on a large set?

Geometric interpretation of $\frac {\partial^2} {\partial x \partial y} f(x,y)$

A quick question about the Hessian matrix

Hessian matrix of a quadratic form

Second order approximation of $\log \det X$

Hessian of restriction of a map to the boundary of a domain

Potential function with a fixed set of minima and no poles.

Where Does the Hessian Matrix Come from (Why Does it Work)?

Hessian for Matrix Factorization objective

Does the positive semidefiniteness of a function not necessarily imply the function is convex?

Computing the diagonal approximation of the Hessian of the Pearson Correlation

Show $f(x) = \frac{1}{2} x_1^2 + \frac{1}{2} x_2^2 - \log(1 + x_1 + x_2)$ is strongly convex and find its parameter.

If $f$ is twice differentiable at $a$, prove $f''(a) vw= \lim_{k \rightarrow \infty} \frac{f(a+t_k(v_k+w_k))-f(a+t_kv_k)-f(a+t_kw_k)+f(a)}{t_k^2}$

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