@inproceedings{47eb146b336e4d24b3fbbdd246ce096a,
title = "Regularized canonical correlations for sensor data clustering",
abstract = "The task of determining informative sensors and clustering the sensor measurements according to their information content is considered. To this end, the standard canonical correlation analysis (CCA) framework is equipped with norm-one and norm-two regularization terms to estimate the unknown number of field sources and identify informative groups of sensors. Coordinate descent techniques are combined with the alternating direction method of multipliers to derive an algorithm that minimizes the regularized CCA framework. An efficient scheme to properly select the regularization coefficients associated with the norm-one and norm-two terms is also developed. Numerical tests corroborate that the novel scheme outperforms existing alternatives.",
keywords = "Canonical correlation analysis, clustering, optimization, sparsity",
author = "Jia Chen and Schizas, {Ioannis D.}",
year = "2015",
month = aug,
day = "4",
doi = "10.1109/ICASSP.2015.7178642",
language = "English (US)",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3601--3605",
booktitle = "2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings",
note = "40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 ; Conference date: 19-04-2014 Through 24-04-2014",
}