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The Consistency Dimension and Distribution-Dependent Learning from Queries (Extended Abstract)

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Book cover Algorithmic Learning Theory (ALT 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1720))

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Abstract

We prove a new combinatorial characterization of polynomial learnability from equivalence queries, and state some of its consequences relating the learnability of a class with the learnability via equivalence and membership queries of its subclasses obtained by restricting the instance space. Then we propose and study two models of query learning in which there is a probability distribution on the instance space, both as an application of the tools developed from the combinatorial characterization and as models of independent interest.

Work supported in part by the EC through the Esprit Program EU BRA program under project 20244 (ALCOM-IT) and the EC Working Group EP27150 (NeuroColt II) and by the spanish DGES PB95-0787 (Koala).

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Author information

Authors and Affiliations

  1. Dept. LSI, Universitat Politècnica de Catalunya, Campus Nord, 08034, Barcelona, Spain

    José L. Balcázar, Jorge Castro & David Guijarro

  2. Fakultät für Informatik, Lehrstuhl Mathematik und Informatik, Ruhr-Universitaet Bochum, D-44780, Bochum

    Hans-Ulrich Simon

Authors
  1. José L. Balcázar
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  2. Jorge Castro
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  3. David Guijarro
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  4. Hans-Ulrich Simon
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Editor information

Editors and Affiliations

  1. Department of Mathematical and Computing Sciences, Tokyo Institute of Technology, Tokyo, 152-8552, Japan

    Osamu Watanabe

  2. Waseda University, 1-6-1 Nishiwaseda, Shinjuku-ku, Tokyo, 169-8050, Japan

    Takashi Yokomori

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© 1999 Springer-Verlag Berlin Heidelberg

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Balcázar, J.L., Castro, J., Guijarro, D., Simon, HU. (1999). The Consistency Dimension and Distribution-Dependent Learning from Queries (Extended Abstract). In: Watanabe, O., Yokomori, T. (eds) Algorithmic Learning Theory. ALT 1999. Lecture Notes in Computer Science(), vol 1720. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46769-6_7

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  • DOI: https://doi.org/10.1007/3-540-46769-6_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66748-3

  • Online ISBN: 978-3-540-46769-4

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