Sequential prediction of binary sequence with side information only

György Ottucsák, László Györfi

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

1 Citation (Scopus)

Abstract

A simple on-line procedure is considered for the prediction of a binary-valued sequence in the setup introduced and studied by Weissman and Merhav [13], [14], where only side information is available for the algorithm. The (non-randomized) algorithm is based on a convex combination of several simple predictors. If the side information is also binary-valued (i.e. original sequence is corrupted by a binary sequence) and both processes are realizations of stationary and ergodic random processes then the average of the loss converges, almost surely, to that of the optimum, given by the Bayes predictor. An analog result is offered for the classification of binary processes.

Original languageEnglish
Title of host publicationProceedings - 2007 IEEE International Symposium on Information Theory, ISIT 2007
Pages2351-2355
Number of pages5
DOIs
Publication statusPublished - Dec 1 2007
Event2007 IEEE International Symposium on Information Theory, ISIT 2007 - Nice, France
Duration: Jun 24 2007Jun 29 2007

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8101

Other

Other2007 IEEE International Symposium on Information Theory, ISIT 2007
CountryFrance
CityNice
Period6/24/076/29/07

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modelling and Simulation
  • Applied Mathematics

Cite this

Ottucsák, G., & Györfi, L. (2007). Sequential prediction of binary sequence with side information only. In Proceedings - 2007 IEEE International Symposium on Information Theory, ISIT 2007 (pp. 2351-2355). [4557170] (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2007.4557170