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Queries Revisited

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Algorithmic Learning Theory (ALT 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2225))

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Abstract

We begin with a brief tutorial on the problem of learning a finite concept class over a finite domain using membership queries and/or equivalence queries. We then sketch general results on the number of queries needed to learn a class of concepts, focusing on the various notions of combinatorial dimension that have been employed, including the teaching dimension, the exclusion dimension, the extended teaching dimension, the fingerprint dimension, the sample exclusion dimension, the Vapnik-Chervonenkis dimension, the abstract identification dimension, and the general dimension.

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Author information

Authors and Affiliations

  1. Computer Science Department, Yale University, P. O. Box 208285, 06520-8285, New Haven, CT, USA

    Dana Angluin

Authors
  1. Dana Angluin
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Editor information

Editors and Affiliations

  1. IBM, Thomas J.Watson Research Center, Room 33-237, P.O.Box 218, 10598, Yorktown, NY, USA

    Naoki Abe

  2. Dept.of Electrical Engineering and Computer Science, Tufts University, 161 College Ave., 02155, Medford, MA, USA

    Roni Khardon

  3. Medizinische Universität zu Lübeck,Inst.für Theoretische Informatik, Wallstr.40, 23560, Lübeck, Germany

    Thomas Zeugmann

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© 2001 Springer-Verlag Berlin Heidelberg

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Angluin, D. (2001). Queries Revisited. In: Abe, N., Khardon, R., Zeugmann, T. (eds) Algorithmic Learning Theory. ALT 2001. Lecture Notes in Computer Science(), vol 2225. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45583-3_3

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  • DOI: https://doi.org/10.1007/3-540-45583-3_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42875-6

  • Online ISBN: 978-3-540-45583-7

  • eBook Packages: Springer Book Archive

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