A sufficient condition for learning unbounded unions of languages with refinement operators

Tomohiko Okayama, Ryo Yoshinaka, Keisuke Otaki, Akihiro Yamamoto

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

This paper presents a natural sufficient condition on a class of languages under which all the unions of any number of languages from the class are learnable from positive examples (data) in the Gold-style. Learning unions of languages models information extraction from mixed data from different sources. The Gold-style learning has provided many fruitful results on learning unions of bounded number of languages, while few positive results on learning unions of unbounded number of languages has been known. In this research, we focus on a condition of the class of languages on which refinement operators are defined. Refinement operators are fundamental tools to transform a hypotheses, which represents a language, into a set of hypotheses, which represent a subsets of the language.

Original languageEnglish
Publication statusPublished - 2014 Jan 1
Externally publishedYes
Event2014 International Symposium on Artificial Intelligence and Mathematics, ISAIM 2014 - Fort Lauderdale, United States
Duration: 2014 Jan 62014 Jan 8

Conference

Conference2014 International Symposium on Artificial Intelligence and Mathematics, ISAIM 2014
Country/TerritoryUnited States
CityFort Lauderdale
Period14/1/614/1/8

ASJC Scopus subject areas

  • Applied Mathematics
  • Artificial Intelligence

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