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On the Learnability of Hidden Markov Models

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Grammatical Inference: Algorithms and Applications (ICGI 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2484))

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Abstract

A simple result is presented that links the learning of hidden Markov models to results in complexity theory about nonlearnability of finite automata under certain cryptographic assumptions. Rather than considering all probability distributions, or even just certain specific ones, the learning of a hidden Markov model takes place under a distribution induced by the model itself.

Supported by a Marie Curie fellowship of the European Union under grant no. ERB-FMBI-CT98-3248. Most of this research was done while the author was working at the University of Munich.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, Vrije Universiteit Amsterdam, De Boelelaan 1081a, 1081 HV, Amsterdam, the Netherlands

    Sebastiaan A. Terwijn

Authors
  1. Sebastiaan A. Terwijn
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Editor information

Editors and Affiliations

  1. Perot Systems Nederland B.V., Hoefseweg 1, 3821 AE, Amersfoort, The Netherlands

    Pieter Adriaans (Senior Research Advisor, Professor of Learning and Adaptive Systems) (Senior Research Advisor, Professor of Learning and Adaptive Systems)

  2. ILLC/Computation and Complexity Theory, Universiteit van Amsterdam, Plantage Muidergracht 24, 1018 TV, Amsterdam, The Netherlands

    Pieter Adriaans (Senior Research Advisor, Professor of Learning and Adaptive Systems) (Senior Research Advisor, Professor of Learning and Adaptive Systems)

  3. School of Electrical Engineering and Computer Science, University of Newcastle, University Drive, Callaghan, NSW, 2308, Australia

    Henning Fernau

  4. Wilhelm-Schickard-Institut für Informatik, Universität Tübingen, Sand 13, 72076, Tübingen, Germany

    Henning Fernau

  5. FNWI/ILLC, Cognitive Systems and Information Processing Group, Universiteit van Amsterdam, Room B-5.39, Nieuwe Achtergracht 166, 1018 WV, Amsterdam, The Netherlands

    Menno van Zaanen

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© 2002 Springer-Verlag Berlin Heidelberg

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Terwijn, S.A. (2002). On the Learnability of Hidden Markov Models. In: Adriaans, P., Fernau, H., van Zaanen, M. (eds) Grammatical Inference: Algorithms and Applications. ICGI 2002. Lecture Notes in Computer Science(), vol 2484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45790-9_21

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  • DOI: https://doi.org/10.1007/3-540-45790-9_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44239-4

  • Online ISBN: 978-3-540-45790-9

  • eBook Packages: Springer Book Archive

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