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Learning PDFA with Asynchronous Transitions

  • Borja Balle
  • Jorge Castro
  • Ricard Gavaldà
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6339)

Abstract

In this paper we extend the PAC learning algorithm due to Clark and Thollard for learning distributions generated by PDFA to automata whose transitions may take varying time lengths, governed by exponential distributions.

Keywords

Exponential Distribution Relative Entropy Alphabet Size Asynchronous Transition Probabilistic Automaton 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Borja Balle
    • 1
  • Jorge Castro
    • 1
  • Ricard Gavaldà
    • 1
  1. 1.Universitat Politècnica de CatalunyaBarcelona

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