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Fast ADMM for semidefinite programs with chordal sparsity

Abstract:

Many problems in control theory can be formulated as semidefinite programs (SDPs). For large-scale SDPs, it is important to exploit the inherent sparsity to improve scalability. This paper develops efficient first-order methods to solve SDPs with chordal sparsity based on the alternating direction method of multipliers (ADMM). We show that chordal decomposition can be applied to either the primal or the dual standard form of a sparse SDP, resulting in scaled versions of ADMM algorithms with t...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.23919/ACC.2017.7963462

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Institution:
University of Oxford
Oxford college:
Worcester College
Role:
Author
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Institution:
University of Oxford
Oxford college:
St Edmund Hall
Role:
Author
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Funding agency for:
Zheng, Y
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Funding agency for:
Zheng, Y
Publisher:
IEEE Publisher's website
Journal:
Proceedings of the American Control Conference Journal website
Pages:
3335-3340
Host title:
Proceedings of the American Control Conference
Publication date:
2017-07-03
Acceptance date:
2017-01-23
DOI:
EISSN:
2378-5861
ISSN:
0743-1619
Source identifiers:
681353
ISBN:
9781509045839
Pubs id:
pubs:681353
UUID:
uuid:8e7d0453-7d23-4394-ba6c-610ca525fa48
Local pid:
pubs:681353
Deposit date:
2017-02-27

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