Question

Sparse representation using overcomplete dictionary - when is L1 norm not good enough?

score 503 · Answer 1 · 2014-07-29 16:23:50

503

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Sparse representation using overcomplete dictionary - when is L1 norm not good enough?

Published on 29 Jul 2014 - 16:23

score 46 · Answer 2 · 2026-03-31 17:20:26

46

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When solving convex problem, why we don't just find the optimal of the cost function and project it back to the feasible set

Published on 31 Mar 2026 - 17:20

score 1k · Answer 3 · 2026-03-29 05:10:30

1k

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Solver for Euclidean Norm Squared Constraint Least Squares

Published on 29 Mar 2026 - 5:10

score 50 · Answer 4 · 2014-08-03 08:51:24

50

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Help needed on convex optimization!!

Published on 03 Aug 2014 - 8:51

score 1k · Answer 5 · 2014-08-04 15:17:50

1k

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What is a $0$-sublevel set?

Published on 04 Aug 2014 - 15:17

score 59 · Answer 6 · 2014-08-05 12:11:52

59

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Can this type of constraint be recasted to a convex constraint?

Published on 05 Aug 2014 - 12:11

score 1.5k · Answer 7 · 2026-03-27 17:06:20

1.5k

Views

Coordinate descent for quadratic cost with $1$-norm regularization and box constraints

Published on 27 Mar 2026 - 17:06

score 489 · Answer 8 · 2014-08-05 21:10:14

489

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$F(x) = f(x) + g(x) + h(x)$, where h(x) is strongly convex , is also strongly convex

Published on 05 Aug 2014 - 21:10

score 169 · Answer 9 · 2026-03-27 23:35:54

169

Views

How to deal with non-existent derivatives in Lagrangian?

Published on 27 Mar 2026 - 23:35

score 1.4k · Answer 10 · 2026-03-25 23:35:43

1.4k

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Free solvers in C/C++ for convex integer programming

Published on 25 Mar 2026 - 23:35

score 638 · Answer 11 · 2026-03-29 14:57:42

638

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Gradient descent (with line search) for convex functions viewed as alternation

Published on 29 Mar 2026 - 14:57

score 306 · Answer 12 · 2026-03-26 17:29:21

306

Views

Knuth's Sandwich Theorem: requesting proof clarification

Published on 26 Mar 2026 - 17:29

score 730 · Answer 13 · 2026-03-25 03:24:19

730

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Farkas's lemma for semidefinite programs

Published on 25 Mar 2026 - 3:24

score 783 · Answer 14 · 2014-08-12 11:41:21

783

Views

Alternating Direction Method of Multipliers (ADMM) application

Published on 12 Aug 2014 - 11:41

score 41 · Answer 15 · 2014-08-12 23:14:32

41

Views

Solve the linear program

Published on 12 Aug 2014 - 23:14

List Question

Sparse representation using overcomplete dictionary - when is L1 norm not good enough?

When solving convex problem, why we don't just find the optimal of the cost function and project it back to the feasible set

Solver for Euclidean Norm Squared Constraint Least Squares

Help needed on convex optimization!!

What is a $0$-sublevel set?

Can this type of constraint be recasted to a convex constraint?

Coordinate descent for quadratic cost with $1$-norm regularization and box constraints

$F(x) = f(x) + g(x) + h(x)$, where h(x) is strongly convex , is also strongly convex

How to deal with non-existent derivatives in Lagrangian?

Free solvers in C/C++ for convex integer programming

Gradient descent (with line search) for convex functions viewed as alternation

Knuth's Sandwich Theorem: requesting proof clarification

Farkas's lemma for semidefinite programs

Alternating Direction Method of Multipliers (ADMM) application

Solve the linear program

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