Learning mildly context-sensitive languages with multidimensional substitutability from positive data

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

16 Citations (Scopus)

Abstract

Recently Clark and Eyraud (2007) have shown that substitutable context-free languages, which capture an aspect of natural language phenomena, are efficiently identifiable in the limit from positive data. Generalizing their work, this paper presents a polynomial-time learning algorithm for new subclasses of mildly context-sensitive languages with variants of substitutability.

Original languageEnglish
Title of host publicationAlgorithmic Learning Theory - 20th International Conference, ALT 2009, Proceedings
Pages278-292
Number of pages15
DOIs
Publication statusPublished - 2009 Dec 1
Externally publishedYes
Event20th International Conference on Algorithmic Learning Theory, ALT 2009 - Porto, Portugal
Duration: 2009 Oct 32009 Oct 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5809 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other20th International Conference on Algorithmic Learning Theory, ALT 2009
Country/TerritoryPortugal
CityPorto
Period09/10/309/10/5

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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