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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