Learning efficiency of very simple grammars from positive data

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

The class of very simple grammars is known to be polynomial-time identifiable in the limit from positive data. This paper gives even more general discussion on the efficiency of identification of very simple grammars from positive data, which includes both positive and negative results. In particular, we present an alternative efficient inconsistent learning algorithm for very simple grammars.

本文言語English
ホスト出版物のタイトルAlgorithmic Learning Theory - 18th International Conference, ALT 2007, Proceedings
出版社Springer Verlag
ページ227-241
ページ数15
ISBN(印刷版)9783540752240
DOI
出版ステータスPublished - 2007
外部発表はい
イベント18th International Conference on Algorithmic Learning Theory, ALT 2007 - Sendai, Japan
継続期間: 2007 10 12007 10 4

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4754 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other18th International Conference on Algorithmic Learning Theory, ALT 2007
国/地域Japan
CitySendai
Period07/10/107/10/4

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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