Online reconstruction from big data via compressive censoring

Gang Wang, Dimitris Berberidis, Vassilis Kekatos, Georgios B. Giannakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

This is an era of data deluge with individuals and pervasive sensors acquiring large and ever-increasing amounts of data. Nevertheless, given the inherent redundancy, the costs related to data acquisition, transmission, and storage can be reduced if the per-datum importance is properly exploited. In this context, the present paper investigates sparse linear regression with censored data that appears naturally under diverse data collection setups. A practical censoring rule is proposed here for data reduction purposes. A sparsity-aware censored maximum-likelihood estimator is also developed, which fits well to big data applications. Building on recent advances in online convex optimization, a novel algorithm is finally proposed to enable real-time processing. The online algorithm applies even to the general censoring setup, while its simple closed-form updates enjoy provable convergence. Numerical simulations corroborate its effectiveness in estimating sparse signals from only a subset of exact observations, thus reducing the processing cost in big data applications.

Original languageEnglish (US)
Title of host publication2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages326-330
Number of pages5
ISBN (Electronic)9781479970889
DOIs
StatePublished - Feb 5 2014
Event2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 - Atlanta, United States
Duration: Dec 3 2014Dec 5 2014

Publication series

Name2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014

Other

Other2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
CountryUnited States
CityAtlanta
Period12/3/1412/5/14

Keywords

  • Compressive sensing
  • Data censoring
  • MLE
  • Online convex optimization

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