Linear coordinate-descent message-passing for quadratic optimization

Zhang, G; Heusdens, R

Linear coordinate-descent message-passing for quadratic optimization

Zhang, G

Heusdens, R

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Publication Type:: Conference Proceeding
Citation:: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2012, pp. 2005 - 2008
Issue Date:: 2012-10-23

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Field	Value	Language
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-4521-542X	en_US
dc.contributor.author	Heusdens, R	en_US
dc.date.issued	2012-10-23	en_US
dc.identifier.citation	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2012, pp. 2005 - 2008	en_US
dc.identifier.isbn	9781467300469	en_US
dc.identifier.issn	1520-6149	en_US
dc.identifier.uri	http://hdl.handle.net/10453/115370
dc.description.abstract	In this paper we propose a new message-passing algorithm for quadratic optimization. The design of the new algorithm is based on linear coordinate-descent between neighboring nodes. The updating messages are in a form of linear functions as compared to the min-sum algorithm of which the messages are in a form of quadratic functions. Therefore, the linear coordinate-descent (LiCD) algorithm has simpler updating rules than the min-sum algorithm. It is shown that when the quadratic matrix is walk-summable, the LiCD algorithm converges. As an application, the LiCD algorithm is utilized in solving general linear systems. The performance of the LiCD algorithm is found empirically to be comparable to that of the min-sum algorithm, but at lower complexity in terms of computation and storage. © 2012 IEEE.	en_US
dc.relation.ispartof	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings	en_US
dc.relation.isbasedon	10.1109/ICASSP.2012.6288301	en_US
dc.title	Linear coordinate-descent message-passing for quadratic optimization	en_US
dc.type	Conference Proceeding
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

In this paper we propose a new message-passing algorithm for quadratic optimization. The design of the new algorithm is based on linear coordinate-descent between neighboring nodes. The updating messages are in a form of linear functions as compared to the min-sum algorithm of which the messages are in a form of quadratic functions. Therefore, the linear coordinate-descent (LiCD) algorithm has simpler updating rules than the min-sum algorithm. It is shown that when the quadratic matrix is walk-summable, the LiCD algorithm converges. As an application, the LiCD algorithm is utilized in solving general linear systems. The performance of the LiCD algorithm is found empirically to be comparable to that of the min-sum algorithm, but at lower complexity in terms of computation and storage. © 2012 IEEE.

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http://hdl.handle.net/10453/115370