List questions from convex-optimization

Published on 13 Apr 2026 - 2:51

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How do you prove that $\{ Ax \mid x \geq 0 \}$ is closed?

Published on 11 Apr 2026 - 20:59

258

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A question about Lagrange multiplier in optimization

Published on 12 Apr 2026 - 3:07

558

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How can I experiment with Lagrange multiplier in QCQP?

Published on 07 Apr 2026 - 22:51

107

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Does projected gradint descent(pgd) results in the same minimizer as the one given by unconstrained gd and projected back on the constrained set?

Published on 15 Apr 2026 - 12:48

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Maximizing a linear function over an ellipsoid

Published on 20 Apr 2026 - 2:20

63

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Is convexity the most general dividing line between "easy" and "hard" optimization problems?

Published on 30 Mar 2026 - 3:54

454

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On accelerated Proximal Gradient Methods

Published on 13 Apr 2026 - 21:10

63

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Demonstrating convexity of a convex optimization problem

Published on 10 Apr 2026 - 15:39

812

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floor/ceiling/round functions in the constraints of an optimization?

Published on 30 Mar 2026 - 13:20

687

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What are spurious local optima?

Published on 12 Apr 2026 - 8:34

48

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Related to Caratheodary theorem

Published on 14 Apr 2026 - 15:40

744

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Is the root of a sum of squared differences convex?

Published on 10 Apr 2026 - 1:26

120

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Why $f:R^2\to R$, with $\mbox{dom} f=R^2_+$ and $f(x_1,x_2) =x_1x_2$ is quasiconcave?

Published on 16 Apr 2026 - 9:24

1k

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Sum/product of two functions of two variables are to be minimized

Published on 11 Apr 2026 - 14:59

List Question

Minimizing a strictly convex function with inequality constraint

How do you prove that $\{ Ax \mid x \geq 0 \}$ is closed?

A question about Lagrange multiplier in optimization

How can I experiment with Lagrange multiplier in QCQP?

Does projected gradint descent(pgd) results in the same minimizer as the one given by unconstrained gd and projected back on the constrained set?

Maximizing a linear function over an ellipsoid

Is convexity the most general dividing line between "easy" and "hard" optimization problems?

On accelerated Proximal Gradient Methods

Demonstrating convexity of a convex optimization problem

floor/ceiling/round functions in the constraints of an optimization?

What are spurious local optima?

Related to Caratheodary theorem

Is the root of a sum of squared differences convex?

Why $f:R^2\to R$, with $\mbox{dom} f=R^2_+$ and $f(x_1,x_2) =x_1x_2$ is quasiconcave?

Sum/product of two functions of two variables are to be minimized

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