List questions from convex-optimization

Published on 12 Apr 2026 - 8:08

138

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Standard duality argument

Published on 14 Apr 2026 - 0:01

383

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Proof of dimension of Polyhedron

Published on 09 Apr 2026 - 20:58

66

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Compute the min of $a^Tx+||x||_{\infty}$

Published on 17 Apr 2026 - 1:13

263

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K is proper cone. K is pointed?

Published on 15 Apr 2026 - 5:31

135

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Sub-differential of a sum of non-convex functions

Published on 16 Apr 2026 - 13:01

71

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Finding the KKT Conditions

Published on 12 Apr 2026 - 7:09

109

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Solve $\min_{\mathbf{V}}~\frac{1}{2}\|\mathbf{Z}-\mathbf{U}\mathbf{V}\mathbf{X}\|_{F}^{2}+\frac{\lambda}{2}\|\mathbf{V}\|_{F}^{2}$

Published on 16 Apr 2026 - 2:02

113

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Convert problem into SDP

Published on 09 Apr 2026 - 6:39

151

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Why is $\lim_{t \to 0} \frac{f(x + t(y-x)) - f(x)}{t} = \nabla f(x)^T\cdot (y-x)$?

Published on 16 Apr 2026 - 3:04

47

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Given $1/2x^TQx+d^Tx$ s.t $a_1^Tx\leq b_1$ $a_2^Tx\leq b_2$ find optimal solution

Published on 16 Apr 2026 - 9:20

37

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Discrete analog of the idea that a convex function has a unique minimum

Published on 11 Apr 2026 - 10:30

251

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Kernel-trick in the primal support vector machine problem

Published on 15 Apr 2026 - 5:32

116

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SCP (Sequential Convex Programming) vs SQP (Sequential Quadratic Programming)

Published on 09 Apr 2026 - 17:43

736

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How do I solve $\min_x \max(c_1^Tx, c_2^Tx, \dots, c_k^Tx)$ for $\lVert x \rVert_2 = 1$.

Published on 16 Apr 2026 - 12:44

List Question

maximum of multivariable convex function

Standard duality argument

Proof of dimension of Polyhedron

Compute the min of $a^Tx+||x||_{\infty}$

K is proper cone. K is pointed?

Sub-differential of a sum of non-convex functions

Finding the KKT Conditions

Solve $\min_{\mathbf{V}}~\frac{1}{2}\|\mathbf{Z}-\mathbf{U}\mathbf{V}\mathbf{X}\|_{F}^{2}+\frac{\lambda}{2}\|\mathbf{V}\|_{F}^{2}$

Convert problem into SDP

Why is $\lim_{t \to 0} \frac{f(x + t(y-x)) - f(x)}{t} = \nabla f(x)^T\cdot (y-x)$?

Given $1/2x^TQx+d^Tx$ s.t $a_1^Tx\leq b_1$ $a_2^Tx\leq b_2$ find optimal solution

Discrete analog of the idea that a convex function has a unique minimum

Kernel-trick in the primal support vector machine problem

SCP (Sequential Convex Programming) vs SQP (Sequential Quadratic Programming)

How do I solve $\min_x \max(c_1^Tx, c_2^Tx, \dots, c_k^Tx)$ for $\lVert x \rVert_2 = 1$.

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