Question

How to maximize $\| {\bf U x}\|^2$ when ${\bf U}$ is a upper triangular matrix

score 75 · Answer 1 · 2026-04-14 14:14:41

75

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How to maximize $\| {\bf U x}\|^2$ when ${\bf U}$ is a upper triangular matrix

Published on 14 Apr 2026 - 14:14

score 37 · Answer 2 · 2026-05-10 17:00:43

37

Views

In order to induce group sparsity, can we use $\left \| A \right \|_{1,1}$ instead of $\left \| A \right \|_{1,2}$?

Published on 10 May 2026 - 17:00

score 1.4k · Answer 3 · 2026-04-14 01:49:12

1.4k

Views

Convex optimization books, except with a focus on problem solving and formalism later?

Published on 14 Apr 2026 - 1:49

score 137 · Answer 4 · 2026-04-11 21:06:13

137

Views

Convex hull of points

Published on 11 Apr 2026 - 21:06

score 428 · Answer 5 · 2026-04-12 10:42:11

428

Views

Question about the dual norm

Published on 12 Apr 2026 - 10:42

score 169 · Answer 6 · 2026-04-14 18:42:00

169

Views

Example of an unbounded convex set with no recession direction?

Published on 14 Apr 2026 - 18:42

score 126 · Answer 7 · 2026-04-10 21:30:32

126

Views

Purpose of the Perturbation function in Convex Optimization

Published on 10 Apr 2026 - 21:30

score 129 · Answer 8 · 2026-04-12 08:09:48

129

Views

Solving SDP as an NLP with squared slack variable

Published on 12 Apr 2026 - 8:09

score 109 · Answer 9 · 2026-04-14 13:42:36

109

Views

Find the dual problem of $\min_x\{||x-a_1||+||x-a_2||+||x-a_3||,a_i\in\mathbb{R}^n\}$

Published on 14 Apr 2026 - 13:42

score 52 · Answer 10 · 2026-04-14 16:26:04

52

Views

The maximum of (Minimum $\times$ Cardinality) Over all Subsets

Published on 14 Apr 2026 - 16:26

score 474 · Answer 11 · 2026-04-14 03:33:58

474

Views

Orthogonal Projection onto a Variation of the Unit Simplex

Published on 14 Apr 2026 - 3:33

score 78 · Answer 12 · 2026-04-11 10:19:29

78

Views

Convex conjugacy and differentiating under the "sup" operator

Published on 11 Apr 2026 - 10:19

score 48 · Answer 13 · 2026-04-16 05:42:05

48

Views

Prove that the optimal value is $f(x)=\sum_{i=1}^{k}x_{[i]}$ where $x_{[i]}$ is the ith largest values in the vector $x$

Published on 16 Apr 2026 - 5:42

score 163 · Answer 14 · 2026-04-28 16:35:39

163

Views

Does symmetry and monotonicity in each argument of a function guarantees Schur Convexity?

Published on 28 Apr 2026 - 16:35

score 196 · Answer 15 · 2026-04-15 13:02:32

196

Views

Are convexity and concavity sufficient or necessary condition for $\min \max = \max \min$

Published on 15 Apr 2026 - 13:02

List Question

How to maximize $\| {\bf U x}\|^2$ when ${\bf U}$ is a upper triangular matrix

In order to induce group sparsity, can we use $\left \| A \right \|_{1,1}$ instead of $\left \| A \right \|_{1,2}$?

Convex optimization books, except with a focus on problem solving and formalism later?

Convex hull of points

Question about the dual norm

Example of an unbounded convex set with no recession direction?

Purpose of the Perturbation function in Convex Optimization

Solving SDP as an NLP with squared slack variable

Find the dual problem of $\min_x\{||x-a_1||+||x-a_2||+||x-a_3||,a_i\in\mathbb{R}^n\}$

The maximum of (Minimum $\times$ Cardinality) Over all Subsets

Orthogonal Projection onto a Variation of the Unit Simplex

Convex conjugacy and differentiating under the "sup" operator

Prove that the optimal value is $f(x)=\sum_{i=1}^{k}x_{[i]}$ where $x_{[i]}$ is the ith largest values in the vector $x$

Does symmetry and monotonicity in each argument of a function guarantees Schur Convexity?

Are convexity and concavity sufficient or necessary condition for $\min \max = \max \min$

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