Online censoring for large-scale regressions

D. Berberidis; G. Wang; G. B. Giannakis; V. Kekatos

doi:10.1109/ACSSC.2014.7094386

Online censoring for large-scale regressions

D. Berberidis
, G. Wang
, G. B. Giannakis
, V. Kekatos

Electrical and Computer Engineering

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

2 Scopus citations

Abstract

As every day 2.5 quintillion bytes of data are generated, the era of Big Data is undoubtedly upon us. Nonetheless, a significant percentage of the data accrued can be omitted while maintaining a certain quality of statistical inference with a limited computational budget. In this context, estimating adaptively high-dimensional signals from massive data observed sequentially is challenging but equally important in practice. The present paper deals with this challenge based on a novel approach that leverages interval censoring for data reduction. An online maximum likelihood, least mean-square (LMS)-type algorithm, and an online support vector regression algorithm are developed for censored data. The proposed algorithms entail simple, low-complexity, closed-form updates, and have provably bounded regret. Simulated tests corroborate their efficacy.

Original language	English (US)
Title of host publication	Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers
Editors	Michael B. Matthews
Publisher	IEEE Computer Society
Pages	14-18
Number of pages	5
ISBN (Electronic)	9781479982974
DOIs	https://doi.org/10.1109/ACSSC.2014.7094386
State	Published - Apr 24 2015
Event	48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - 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

Other

Other	48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
Country/Territory	United States
City	Pacific Grove
Period	11/2/14 → 11/5/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

D.4. Adaptive Filtering
Technical Area

Publisher link

10.1109/ACSSC.2014.7094386

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Berberidis, D., Wang, G., Giannakis, G. B., & Kekatos, V. (2015). Online censoring for large-scale regressions. In M. B. Matthews (Ed.), Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers (pp. 14-18). Article 7094386 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2015-April). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2014.7094386

Online censoring for large-scale regressions. / Berberidis, D.; Wang, G.; Giannakis, G. B. et al.
Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers. ed. / Michael B. Matthews. IEEE Computer Society, 2015. p. 14-18 7094386 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2015-April).

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

Berberidis, D, Wang, G, Giannakis, GB & Kekatos, V 2015, Online censoring for large-scale regressions. in MB Matthews (ed.), Conference Record of the 48th Asilomar Conference on Signals, Systems and Computers., 7094386, Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2015-April, IEEE Computer Society, pp. 14-18, 48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015, Pacific Grove, United States, 11/2/14. https://doi.org/10.1109/ACSSC.2014.7094386

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Online censoring for large-scale regressions

Abstract

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Bibliographical note

Keywords

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