List questions from convex-optimization

Published on 24 Mar 2026 - 23:56

22

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Optimality Conditions of $ l_{\infty}$ minimization problem

Published on 25 Mar 2026 - 17:38

598

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Math and linear algebra prerequisites for convex optimization

Published on 22 May 2018 - 20:07

47

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Trying to solve a feasiblity SDP

Published on 24 Mar 2026 - 20:46

4k

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What is a bi-affine classifier?

Published on 23 May 2018 - 3:25

223

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Continuity of support functionals

Published on 23 May 2018 - 10:40

180

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Lagrange Multipliers for two constraints, degenerate case

Published on 23 May 2018 - 11:39

309

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How to check if point is a vertex of a set

Published on 23 May 2018 - 18:06

387

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Cost function with unique solution plus convex function has a unique solution?

Published on 25 Mar 2026 - 4:35

82

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proper domain for convex perspective function

Published on 24 May 2018 - 23:57

198

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Showing that the Hausdorff distance from the subdifferential to $0$ is bounded.

Published on 25 Mar 2026 - 6:05

175

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Show $\max_{r\equiv (r_1,..., r_M) \in \mathbb{R}^M} \sum_{k=1}^M \mu_k r_k - \log\Big(\sum_{k=1}^M \exp(r_k) \Big)= \sum_{k=1}^M \mu_k \log(\mu_k)$

Published on 26 Mar 2026 - 12:50

112

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Infimum of $\max(0,y) + \frac{1}{2t}(x-y)^2$

Published on 25 Mar 2026 - 21:49

1.3k

Views

piecewise linear constraints and equivalent linear constraints

Published on 26 May 2018 - 6:44

1.2k

Views

Why it is necessary to maximize and then minimize Lagrangian in hard margin SVM?

Published on 25 Mar 2026 - 3:07

List Question

Is the convex hull of closed cones closed?

Optimality Conditions of $ l_{\infty}$ minimization problem

Math and linear algebra prerequisites for convex optimization

Trying to solve a feasiblity SDP

What is a bi-affine classifier?

Continuity of support functionals

Lagrange Multipliers for two constraints, degenerate case

How to check if point is a vertex of a set

Cost function with unique solution plus convex function has a unique solution?

proper domain for convex perspective function

Showing that the Hausdorff distance from the subdifferential to $0$ is bounded.

Show $\max_{r\equiv (r_1,..., r_M) \in \mathbb{R}^M} \sum_{k=1}^M \mu_k r_k - \log\Big(\sum_{k=1}^M \exp(r_k) \Big)= \sum_{k=1}^M \mu_k \log(\mu_k)$

Infimum of $\max(0,y) + \frac{1}{2t}(x-y)^2$

piecewise linear constraints and equivalent linear constraints

Why it is necessary to maximize and then minimize Lagrangian in hard margin SVM?

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