Presentation 1994/10/21
Learning Orthogonal F-Horn Formulas
Akira Miyashiro, Eiji Takimoto, Yoshifumi Sakai, Akira Maruoka,
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Abstract(in English) In the PAC-learning,or the query learning model,it has been an important open problem to decide whether the class of DNF or CNF formulas is learnable.Recently,it was pointed out that the problem of PAC-learning for these classes with membership queries can be reduced to that of query learning for the class of k-quasi Horn formulas with membership and equivalence queries.A k-quasi Horn formula is a CNF formula with each clause containing at most k positive literals.In this paper,a notion of F-Horn formulas,which is an extention of k-quasi formulas,is introduced,and,it is shown that under some condition,the class of orthogonal F-Horn formulas is learnable with membership,equivalence and subset queries.
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Keyword(in English) query learning / PAC-learning / Computational learning theory / Horn formulas / DNF formulas
Paper # COMP94-45
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Committee COMP
Conference Date 1994/10/21(1days)
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Registration To Theoretical Foundations of Computing (COMP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Learning Orthogonal F-Horn Formulas
Sub Title (in English)
Keyword(1) query learning
Keyword(2) PAC-learning
Keyword(3) Computational learning theory
Keyword(4) Horn formulas
Keyword(5) DNF formulas
1st Author's Name Akira Miyashiro
1st Author's Affiliation Hitachi Research Laboratory,Hitachi Ltd.()
2nd Author's Name Eiji Takimoto
2nd Author's Affiliation Graduate School of Information Sciences,Tohoku University
3rd Author's Name Yoshifumi Sakai
3rd Author's Affiliation Graduate School of Information Sciences,Tohoku University
4th Author's Name Akira Maruoka
4th Author's Affiliation Graduate School of Information Sciences,Tohoku University
Date 1994/10/21
Paper # COMP94-45
Volume (vol) vol.94
Number (no) 304
Page pp.pp.-
#Pages 9
Date of Issue