Adaptive regularized canonical correlations in clustering sensor data

Jia Chen; Ioannis D. Schizas

doi:10.1109/ACSSC.2014.7094738

Adaptive regularized canonical correlations in clustering sensor data

Jia Chen
, Ioannis D. Schizas

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A regularized canonical correlations scheme is proposed for adaptive clustering of sensor measurements according to their information content. A novel framework utilizing sparsity-inducing regularization and exponential weighing is designed to deal with nonstationary settings. Distributed recursions to minimize the proposed formulation are put forth by utilizing coordinate descent techniques combined with the alternating direction method of multipliers. Numerical tests demonstrate that the novel adaptive clustering framework is capable to deal with nonstationary settings while outperforming existing alternatives.

Original language	English (US)
Title of host publication	Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2014
Editors	Michael B. Matthews
Publisher	IEEE Computer Society
Pages	1611-1615
Number of pages	5
ISBN (Electronic)	9781479982974
DOIs	https://doi.org/10.1109/ACSSC.2014.7094738
State	Published - Apr 24 2015
Externally published	Yes
Event	48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2014 - Pacific Grove, United States Duration: Nov 2 2014 → Nov 5 2014

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
Volume	2015-April
ISSN (Print)	1058-6393
ISSN (Electronic)	2576-2303

Conference

Conference	48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2014
Country/Territory	United States
City	Pacific Grove
Period	11/2/14 → 11/5/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

Adaptive
canonical correlation analysis
non-stationary data
sparsity

Publisher link

10.1109/ACSSC.2014.7094738

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Chen, J., & Schizas, I. D. (2015). Adaptive regularized canonical correlations in clustering sensor data. In M. B. Matthews (Ed.), Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2014 (pp. 1611-1615). Article 7094738 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2015-April). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2014.7094738

Adaptive regularized canonical correlations in clustering sensor data. / Chen, Jia; Schizas, Ioannis D.
Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2014. ed. / Michael B. Matthews. IEEE Computer Society, 2015. p. 1611-1615 7094738 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2015-April).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chen, J & Schizas, ID 2015, Adaptive regularized canonical correlations in clustering sensor data. in MB Matthews (ed.), Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2014., 7094738, Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2015-April, IEEE Computer Society, pp. 1611-1615, 48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2014, Pacific Grove, United States, 11/2/14. https://doi.org/10.1109/ACSSC.2014.7094738

Chen J, Schizas ID. Adaptive regularized canonical correlations in clustering sensor data. In Matthews MB, editor, Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2014. IEEE Computer Society. 2015. p. 1611-1615. 7094738. (Conference Record - Asilomar Conference on Signals, Systems and Computers). doi: 10.1109/ACSSC.2014.7094738

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Adaptive regularized canonical correlations in clustering sensor data

Abstract

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Keywords

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