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Learning Weighted Automata

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Algebraic Informatics (CAI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9270))

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Abstract

Weighted finite automata (WFA) are finite automata whose transitions and states are augmented with some weights, elements of a semiring. A WFA induces a function over strings. The value it assigns to an input string is the semiring sum of the weights of all paths labeled with that string, where the weight of a path is obtained by taking the semiring product of the weights of its constituent transitions, as well as those of its origin and destination states.

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Author information

Authors and Affiliations

  1. School of Computer Science, McGill University, Montréal, Canada

    Borja Balle

  2. Courant Institute of Mathematical Sciences, New York, NY, USA

    Mehryar Mohri

  3. Google Research, New York, NY, USA

    Mehryar Mohri

Authors
  1. Borja Balle
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  2. Mehryar Mohri
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Correspondence to Mehryar Mohri .

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Editors and Affiliations

  1. Institut für Maschinelle, Universität Stuttgart, Stuttgart, Baden-Württemberg, Germany

    Andreas Maletti

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Balle, B., Mohri, M. (2015). Learning Weighted Automata. In: Maletti, A. (eds) Algebraic Informatics. CAI 2015. Lecture Notes in Computer Science(), vol 9270. Springer, Cham. https://doi.org/10.1007/978-3-319-23021-4_1

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  • DOI: https://doi.org/10.1007/978-3-319-23021-4_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23020-7

  • Online ISBN: 978-3-319-23021-4

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