Inferring probabilistic acyclic automata using the minimum description length principle

Yoram Singer, Naftali Tishby

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

Abstract

The use of Rissanen's (1978) minimum description length principle for the construction of probabilistic acyclic automata (PAA) is explored. We propose a learning algorithm for a PAA that is adaptive both in the structure and the dimension of the model. The proposed algorithm was tested on synthetic data as well as on real pattern recognition problems.

Original languageEnglish (US)
Title of host publicationProceedings - 1994 IEEE International Symposium on Information Theory, ISIT 1994
Number of pages1
DOIs
StatePublished - Dec 1 1994
Externally publishedYes
Event1994 IEEE International Symposium on Information Theory, ISIT 1994 - Trondheim, Norway
Duration: Jun 27 1994Jul 1 1994

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Other

Other1994 IEEE International Symposium on Information Theory, ISIT 1994
CountryNorway
CityTrondheim
Period6/27/947/1/94

All Science Journal Classification (ASJC) codes

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

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    Singer, Y., & Tishby, N. (1994). Inferring probabilistic acyclic automata using the minimum description length principle. In Proceedings - 1994 IEEE International Symposium on Information Theory, ISIT 1994 [394627] (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.1994.394627