List questions from convex-optimization

Published on 26 Mar 2026 - 22:19

69

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max of a convex function

Published on 26 Mar 2026 - 6:16

850

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Sufficient condition for convex conjugate to be second-order differentiable

Published on 25 Oct 2019 - 11:36

1k

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Projection of a symmetric matrix onto the positive semidefinite (PSD) cone under the nuclear norm

Published on 25 Oct 2019 - 19:21

57

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Prove that $S=\{x=(x_0,x_1,\dots), x_i\in R; \lim_{i\to\infty}x_i=0\}$ is not strictly convex.

Published on 25 Oct 2019 - 19:42

82

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Convexity of combination of natural logs with sums function

Published on 27 Mar 2026 - 22:12

94

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Minimize $\sum_{i=1}^k\sum_{j=1}^kb_jc_{ij}v_iw_j^2$ subject to $\sum_{i=1}^kv_i=\sum_{j=1}^kw_j=1$

Published on 26 Mar 2026 - 6:16

63

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Least Squares Solution with Three Matrices Involved

Published on 29 Mar 2026 - 15:22

164

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Slater's condition for problem with only one feasible solution

Published on 29 Mar 2026 - 20:03

54

Views

Is solving a convex optimisation for variables in $\mathbb{Q}$ just as hard as $\mathbb{Z}$?

Published on 30 Mar 2026 - 5:28

197

Views

QCQP Convex quadratic optimisation with quadratic constraint

Published on 26 Mar 2026 - 6:31

40

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Convert an optimal basis from Simplex to an actual solution

Published on 25 Mar 2026 - 21:51

60

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How to show that this set is closed?

Published on 29 Oct 2019 - 5:20

234

Views

Absolute value minimization with non-convex constraint

Published on 27 Mar 2026 - 10:08

50

Views

Continuity is not guaranteed even when the function is closed and convex. Why?

Published on 29 Oct 2019 - 11:16

List Question

Simple implementation of interior point method

max of a convex function

Sufficient condition for convex conjugate to be second-order differentiable

Projection of a symmetric matrix onto the positive semidefinite (PSD) cone under the nuclear norm

Prove that $S=\{x=(x_0,x_1,\dots), x_i\in R; \lim_{i\to\infty}x_i=0\}$ is not strictly convex.

Convexity of combination of natural logs with sums function

Minimize $\sum_{i=1}^k\sum_{j=1}^kb_jc_{ij}v_iw_j^2$ subject to $\sum_{i=1}^kv_i=\sum_{j=1}^kw_j=1$

Least Squares Solution with Three Matrices Involved

Slater's condition for problem with only one feasible solution

Is solving a convex optimisation for variables in $\mathbb{Q}$ just as hard as $\mathbb{Z}$?

QCQP Convex quadratic optimisation with quadratic constraint

Convert an optimal basis from Simplex to an actual solution

How to show that this set is closed?

Absolute value minimization with non-convex constraint

Continuity is not guaranteed even when the function is closed and convex. Why?

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