PAC learning of some subclasses of context-free grammars with basic distributional properties from positive data

Chihiro Shibata, Ryo Yoshinaka

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

6 Citations (Scopus)

Abstract

In recent years different interesting subclasses of cfls have been found to be learnable by techniques generically called distributional learning. The theoretical study on the exact learning of cfls by those techniques under different learning scheme is now quite mature. On the other hand, positive results on the pac learnability of cfls are rather limited and quite weak. This paper shows that several subclasses of context-free languages that are known to be exactly learnable with membership queries by distributional learning techniques are pac learnable from positive data under some assumptions on the string distribution.

Original languageEnglish
Title of host publicationAlgorithmic Learning Theory - 24th International Conference, ALT 2013, Proceedings
Pages143-157
Number of pages15
DOIs
Publication statusPublished - 2013 Nov 18
Externally publishedYes
Event24th International Conference on Algorithmic Learning Theory, ALT 2013 - Singapore, Singapore
Duration: 2013 Oct 62013 Oct 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8139 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other24th International Conference on Algorithmic Learning Theory, ALT 2013
CountrySingapore
CitySingapore
Period13/10/613/10/9

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Shibata, C., & Yoshinaka, R. (2013). PAC learning of some subclasses of context-free grammars with basic distributional properties from positive data. In Algorithmic Learning Theory - 24th International Conference, ALT 2013, Proceedings (pp. 143-157). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8139 LNAI). https://doi.org/10.1007/978-3-642-40935-6_11