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A Novel Approach for Solving Convex Problems with Cardinality Constraints

Abstract:

In this paper we consider the problem of minimizing a convex differentiable function subject to sparsity constraints. Such constraints are non-convex and the resulting optimization problem is known to be hard to solve. We propose a novel generalization of this problem and demonstrate that it is equivalent to the original sparsity-constrained problem if a certain weighting term is sufficiently large. We use the proximal gradient method to solve our generalized problem, and show that under cert...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.ifacol.2017.08.2174

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Name:
European Commission
Grant:
PredictiveControl(TEMPO
FP7-PEOPLE-2013-ITNno.607957[TraininginEmbeddedOptimization
Publisher:
Elsevier
Host title:
IFAC 2017: 20th World Congress of the International Federation of Automatic Control
Journal:
IFAC 2017 More from this journal
Volume:
50
Issue:
1
Pages:
13182-13187
Publication date:
2017-10-18
Acceptance date:
2017-02-27
DOI:
Keywords:
Pubs id:
pubs:687452
UUID:
uuid:f5efd802-f1cf-4744-b06e-861d8235b66e
Local pid:
pubs:687452
Source identifiers:
687452
Deposit date:
2017-03-30

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