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An Application of Codes to Attribute-Efficient Learning

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Computational Learning Theory (EuroCOLT 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1572))

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Abstract

We design asymptotically optimal query strategies for the class of parity functions which contain at most k essential variables. The number of questions asked is at most twice the number asked by an optimal strategy. The strategy presented is even non-adaptive. For fixed k, the number of questions is optimal up to additive constants. Our results improve upon results by Uehara, Tsuchida and Wegener [6].

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References

  1. N. Alon, L. Babai and A. Itai, A Fast and Simple Randomized Parallel Algorithm for the Maximal Independent Set Problem, Journal of Algorithms 7, 1986, 567–583.

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  2. P. Damaschke, Adaptive Versus Nonadaptive Attribute-Efficient Learning, Proc. of the 30th Annual ACM Symposium on the Theory of Computing (STOC), 1998, 590–596.

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  3. D. Hoffman, D. Leonard, C. Lindner, K. Phelps, C. Rodger and J. Wall, Coding Theory, the Essentials, Marcel Dekker, 1991.

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  4. R. Lidl and H. Niederreiter, Introduction to Finite Fields and Their Applications, Cambridge University Press, 1994.

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  5. W. Peterson and E. Weldon, Error-Correcting Codes, MIT Press, 2nd edition, 1972.

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  6. R. Uehara, K. Tsuchida and I. Wegener, Identification of Partial Disjunction, Parity, and Threshold Functions, Proc. of the European Conference on Computational Learning Theory (Eurocolt), 1997, 171–184. To appear in Theoretical Computer Science.

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Author information

Authors and Affiliations

  1. Informatik 2, Universität Dortmund, D, 44221, Dortmund, Germany

    Thomas Hofmeister

Authors
  1. Thomas Hofmeister
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Editor information

Editors and Affiliations

  1. Lehrstuhl für Informatik II, Universität Dortmund, D-44221, Dortmund, Germany

    Paul Fischer

  2. Fakultät für Mathematik, Ruhr Universität Bochum, D-44780, Bochum, Germany

    Hans Ulrich Simon

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© 1999 Springer-Verlag Berlin Heidelberg

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Hofmeister, T. (1999). An Application of Codes to Attribute-Efficient Learning. In: Fischer, P., Simon, H.U. (eds) Computational Learning Theory. EuroCOLT 1999. Lecture Notes in Computer Science(), vol 1572. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49097-3_9

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  • DOI: https://doi.org/10.1007/3-540-49097-3_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65701-9

  • Online ISBN: 978-3-540-49097-5

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