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Conference Paper

Algorithms for Learning Function Distinguishable Regular Languages

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons84152

Fernau,  H
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84152

Radl,  A
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Fernau, H., & Radl, A. (2002). Algorithms for Learning Function Distinguishable Regular Languages. Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshops SSPR 2002 and SPR 2002, 64-73.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-DF34-9
Abstract
Function distinguishable languages were introduced as a new methodology of defining characterizable subclasses of the regular languages which are learnable from text. Here, we give details on the implementation and the analysis of the corresponding learning algorithms. We also discuss problems which might occur in practical applications.