Question

Entropy expression optimization with Langrange multipliers

score 294 · Answer 1 · 2026-04-09 21:12:17

294

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Entropy expression optimization with Langrange multipliers

Published on 09 Apr 2026 - 21:12

score 385 · Answer 2 · 2026-04-09 20:33:51

385

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Efficient Algorithm For Projection Onto A Convex Set

Published on 09 Apr 2026 - 20:33

score 71 · Answer 3 · 2026-04-14 03:17:29

71

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Convex programming when the problem has an underlying combinatorial structure that's a DAG

Published on 14 Apr 2026 - 3:17

score 156 · Answer 4 · 2026-04-16 10:10:41

156

Views

Degeneracy of the analytic center of a set of linear inequalities

Published on 16 Apr 2026 - 10:10

score 339 · Answer 5 · 2026-04-17 01:39:45

339

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Going in the direction of the gradient

Published on 17 Apr 2026 - 1:39

score 5.5k · Answer 6 · 2026-04-10 06:52:29

5.5k

Views

What Is the Motivation of Proximal Mapping / Proximal Operator?

Published on 10 Apr 2026 - 6:52

score 1.4k · Answer 7 · 2026-05-11 04:58:10

1.4k

Views

Solving Linearly Constrained Quadratic Programming with Coordinate Descent

Published on 11 May 2026 - 4:58

score 39 · Answer 8 · 2026-04-14 09:19:45

39

Views

In an engineering/optimisation context, does set $E$ have any special significance?

Published on 14 Apr 2026 - 9:19

score 540 · Answer 9 · 2026-04-11 08:43:25

540

Views

Simple example where strong convexity is necessary over strict (or even regular) convexity.

Published on 11 Apr 2026 - 8:43

score 667 · Answer 10 · 2026-04-10 06:19:54

667

Views

Bivariate function maximization

Published on 10 Apr 2026 - 6:19

score 1.4k · Answer 11 · 2026-04-12 17:55:35

1.4k

Views

What is a good technique to decide step size in sub-gradient method for dual decomposition?

Published on 12 Apr 2026 - 17:55

score 1.7k · Answer 12 · 2026-04-14 20:09:30

1.7k

Views

Projected Gradient Method with Multiple Constraints (Projection of Each Row to the Unit Simplex)

Published on 14 Apr 2026 - 20:09

score 237 · Answer 13 · 2026-04-15 06:17:14

237

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Find a vector such that its matrix product is positive in every element

Published on 15 Apr 2026 - 6:17

score 2.1k · Answer 14 · 2026-04-14 06:49:37

2.1k

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Least Squares with $ {L}_{1} $ Regularization (Lasso) and Linear Inequality Constraints

Published on 14 Apr 2026 - 6:49

score 7k · Answer 15 · 2026-05-10 20:08:39

7k

Views

LP relaxation for integer linear programming (ILP)

Published on 10 May 2026 - 20:08

List Question

Entropy expression optimization with Langrange multipliers

Efficient Algorithm For Projection Onto A Convex Set

Convex programming when the problem has an underlying combinatorial structure that's a DAG

Degeneracy of the analytic center of a set of linear inequalities

Going in the direction of the gradient

What Is the Motivation of Proximal Mapping / Proximal Operator?

Solving Linearly Constrained Quadratic Programming with Coordinate Descent

In an engineering/optimisation context, does set $E$ have any special significance?

Simple example where strong convexity is necessary over strict (or even regular) convexity.

Bivariate function maximization

What is a good technique to decide step size in sub-gradient method for dual decomposition?

Projected Gradient Method with Multiple Constraints (Projection of Each Row to the Unit Simplex)

Find a vector such that its matrix product is positive in every element

Least Squares with $ {L}_{1} $ Regularization (Lasso) and Linear Inequality Constraints

LP relaxation for integer linear programming (ILP)

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