Synthesizing enumeration techniques for language learning

Ganesh Baliga, John Case, Sanjay Jain

Research output: Contribution to conferencePaper

14 Scopus citations

Abstract

This paper provides positive and negative results on algorithmically synthesizing, from grammars and from decision procedures for classes and languages, learning machines for identifying, from positive data, grammars for the languages in those classes. In the process, the uniformly decidable classes of recursive languages that can be behaviorally correctly identified from positive data are surprisingly characterized by Angluin's 1980 Condition 2 (the subset for principle for preventing over generalization).

Original languageEnglish (US)
Pages169-180
Number of pages12
StatePublished - Dec 1 1996
EventProceedings of the 1996 9th Annual Conference on Computational Learning Theory - Desenzano del Garda, Italy
Duration: Jun 28 1996Jul 1 1996

Other

OtherProceedings of the 1996 9th Annual Conference on Computational Learning Theory
CityDesenzano del Garda, Italy
Period6/28/967/1/96

All Science Journal Classification (ASJC) codes

  • Computational Mathematics

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    Baliga, G., Case, J., & Jain, S. (1996). Synthesizing enumeration techniques for language learning. 169-180. Paper presented at Proceedings of the 1996 9th Annual Conference on Computational Learning Theory, Desenzano del Garda, Italy, .