Data sketching for tracking large-scale dynamical processes

Dimitrios Berberidis; Georgios B. Giannakis

doi:10.1109/ACSSC.2015.7421144

Data sketching for tracking large-scale dynamical processes

Dimitrios Berberidis, Georgios B. Giannakis

Electrical and Computer Engineering

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

1 Scopus citations

Abstract

In a time when data increase massively in their volume, variety, and velocity, performing inference tasks by utilizing the available information in its entirety is not always an affordable option. The present paper proposes a data-driven measurement selection scheme to render tracking of large-scale dynamic processes affordable, by processing a reduced number of data. The proposed method processes observations sequentially, and extracts a low-complexity sketch that can be implemented in real-time. Furthermore, a low-complexity smoothing is developed as a means of mitigating the error performance degradation caused by dimensionality reduction. Simulations on synthetic data, compare the proposed methods with competing alternatives, and corroborate their efficacy in terms of estimation accuracy versus complexity reduction.

Original language	English (US)
Title of host publication	Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
Editors	Michael B. Matthews
Publisher	IEEE Computer Society
Pages	345-349
Number of pages	5
ISBN (Electronic)	9781467385763
DOIs	https://doi.org/10.1109/ACSSC.2015.7421144
State	Published - Feb 26 2016
Event	49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States Duration: Nov 8 2015 → Nov 11 2015

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
Volume	2016-February
ISSN (Print)	1058-6393

Other

Other	49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
Country/Territory	United States
City	Pacific Grove
Period	11/8/15 → 11/11/15

Bibliographical note

Funding Information:
Work in this paper was supported by NSF Grants No. 1514056 and 1500713, and NIH Grant No. 1R01GM104975-01

Publisher Copyright:
© 2015 IEEE.

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Berberidis, D., & Giannakis, G. B. (2016). Data sketching for tracking large-scale dynamical processes. In M. B. Matthews (Ed.), Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 (pp. 345-349). Article 7421144 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2016-February). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2015.7421144

Data sketching for tracking large-scale dynamical processes. / Berberidis, Dimitrios; Giannakis, Georgios B.
Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015. ed. / Michael B. Matthews. IEEE Computer Society, 2016. p. 345-349 7421144 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2016-February).

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

Berberidis, D & Giannakis, GB 2016, Data sketching for tracking large-scale dynamical processes. in MB Matthews (ed.), Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015., 7421144, Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2016-February, IEEE Computer Society, pp. 345-349, 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015, Pacific Grove, United States, 11/8/15. https://doi.org/10.1109/ACSSC.2015.7421144

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Data sketching for tracking large-scale dynamical processes

Abstract

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