Learning monotone log-term DNF formulas

Yoshifumi Sakai, Akira Maruoka

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

    6 Citations (Scopus)

    Abstract

    Based on the uniform distribution PAC learning model, the learnability for monotone disjunctive normal form formulas with at most O(logn) terms (O(log n)-term MDNF) is investigated. Using the technique of restriction, an algorithm that learns O(logn)-term MDNF in polynomial time is given.

    Original languageEnglish
    Title of host publicationProceedings of the 7th Annual Conference on Computational Learning Theory, COLT 1994
    PublisherAssociation for Computing Machinery
    Pages165-172
    Number of pages8
    ISBN (Electronic)0897916557
    DOIs
    Publication statusPublished - 1994 Jul 16
    Event7th Annual Conference on Computational Learning Theory, COLT 1994 - New Brunswick, United States
    Duration: 1994 Jul 121994 Jul 15

    Publication series

    NameProceedings of the Annual ACM Conference on Computational Learning Theory
    VolumePart F129415

    Other

    Other7th Annual Conference on Computational Learning Theory, COLT 1994
    Country/TerritoryUnited States
    CityNew Brunswick
    Period94/7/1294/7/15

    ASJC Scopus subject areas

    • Software
    • Theoretical Computer Science
    • Artificial Intelligence

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