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Statistical inductive learning of regular formal languages

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Grammatical Inference and Applications (ICGI 1994)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 862))

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Abstract

The estimation problem of probabilistic grammar through the forward-backward algorithm does not guarantee that a global maximum is achieved [12]. In this process, which is based on a gradient descent technique, the initialization is a crucial aspect. In this paper, we show experimentally how the results obtained by this method can be improved when structural information about the task is inductively incorporated in the initial models to be learnt.

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Author information

Authors and Affiliations

  1. Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Camino de Vera s/n, 46071, Valencia, Spain

    Juan Andrés Sánchez & José Miguel Benedí

Authors
  1. Juan Andrés Sánchez
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  2. José Miguel Benedí
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Editor information

Rafael C. Carrasco Jose Oncina

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© 1994 Springer-Verlag Berlin Heidelberg

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Sánchez, J.A., Benedí, J.M. (1994). Statistical inductive learning of regular formal languages. In: Carrasco, R.C., Oncina, J. (eds) Grammatical Inference and Applications. ICGI 1994. Lecture Notes in Computer Science, vol 862. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58473-0_143

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  • DOI: https://doi.org/10.1007/3-540-58473-0_143

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58473-5

  • Online ISBN: 978-3-540-48985-6

  • eBook Packages: Springer Book Archive

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