Question

Convex optimization: Piece-wise, quadratic objective

score 392 · Answer 1 · 2026-03-28 16:56:31

392

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Convex optimization: Piece-wise, quadratic objective

Published on 28 Mar 2026 - 16:56

score 235 · Answer 2 · 2026-03-26 02:48:49

235

Views

Thr Proximal Operator for $ {L}_{1} $ Regularized Least squares Problem

Published on 26 Mar 2026 - 2:48

score 1.2k · Answer 3 · 2026-03-29 14:57:47

1.2k

Views

Is a convex cone a convex polyhedron?

Published on 29 Mar 2026 - 14:57

score 739 · Answer 4 · 2026-04-09 23:00:28

739

Views

Some intuition on the support function of a convex set

Published on 09 Apr 2026 - 23:00

score 76 · Answer 5 · 2026-04-15 06:37:16

76

Views

Is there a way to determine if the Convex Hull of two polyhedra is going to be huge?

Published on 15 Apr 2026 - 6:37

score 188 · Answer 6 · 2026-04-16 14:32:07

188

Views

$\big\langle\nabla f(x)-\nabla f(y),\,(x-y)\big\rangle\ge m\,\left\| x-y\right\|^2,\;m>0\;$ for strictly and strong convex function

Published on 16 Apr 2026 - 14:32

score 605 · Answer 7 · 2026-04-12 19:01:48

605

Views

characteristic cone of polyhedral

Published on 12 Apr 2026 - 19:01

score 265 · Answer 8 · 2026-04-09 15:47:04

265

Views

How to form a dual problem in convex optimization (in a broad view)

Published on 09 Apr 2026 - 15:47

score 26 · Answer 9 · 2026-04-17 10:41:18

26

Views

Variant of conjugate function: $V(s) = \underset{x}\max \{\langle s,x-x_0\rangle-\beta f(x)\}$

Published on 17 Apr 2026 - 10:41

score 2.7k · Answer 10 · 2026-04-17 11:46:02

2.7k

Views

Can you prove that this function is convex? $\sqrt{2x_1^2+3x_2^2+x_3^2+4x_1x_2+7} + (x_1^2+x_2^2+x_3^2+1)^2$.

Published on 17 Apr 2026 - 11:46

score 103 · Answer 11 · 2026-04-17 04:57:48

103

Views

When does a variable goes out with the revised Simplex method?

Published on 17 Apr 2026 - 4:57

score 193 · Answer 12 · 2026-04-11 21:41:38

193

Views

Is the minimum point of a strictly convex function stable?

Published on 11 Apr 2026 - 21:41

score 170 · Answer 13 · 2026-04-15 14:35:21

170

Views

Scalar Least Absolute Deviation (LAD) Analytical Minimization

Published on 15 Apr 2026 - 14:35

score 120 · Answer 14 · 2026-04-09 20:10:31

120

Views

Chebyshev's approximation understanding

Published on 09 Apr 2026 - 20:10

score 383 · Answer 15 · 2026-04-12 06:40:07

383

Views

Use of binary variables in LP problems

Published on 12 Apr 2026 - 6:40

List Question

Convex optimization: Piece-wise, quadratic objective

Thr Proximal Operator for $ {L}_{1} $ Regularized Least squares Problem

Is a convex cone a convex polyhedron?

Some intuition on the support function of a convex set

Is there a way to determine if the Convex Hull of two polyhedra is going to be huge?

$\big\langle\nabla f(x)-\nabla f(y),\,(x-y)\big\rangle\ge m\,\left\| x-y\right\|^2,\;m>0\;$ for strictly and strong convex function

characteristic cone of polyhedral

How to form a dual problem in convex optimization (in a broad view)

Variant of conjugate function: $V(s) = \underset{x}\max \{\langle s,x-x_0\rangle-\beta f(x)\}$

Can you prove that this function is convex? $\sqrt{2x_1^2+3x_2^2+x_3^2+4x_1x_2+7} + (x_1^2+x_2^2+x_3^2+1)^2$.

When does a variable goes out with the revised Simplex method?

Is the minimum point of a strictly convex function stable?

Scalar Least Absolute Deviation (LAD) Analytical Minimization

Chebyshev's approximation understanding

Use of binary variables in LP problems

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