Learning Sequential Tree-to-Word Transducers

Grégoire Laurence; Aurélien Lemay; Joachim Niehren; Slawek Staworko; Marc Tommasi

doi:10.1007/978-3-319-04921-2_40

Learning Sequential Tree-to-Word Transducers

Grégoire Laurence, Aurélien Lemay, Joachim Niehren, Slawek Staworko, Marc Tommasi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We study the problem of learning sequential top-down tree-to-word transducers (stws). First, we present a Myhill-Nerode characterization of the corresponding class of sequential tree-to-word transformations ( TeX ). Next, we investigate what learning of stws means, identify fundamental obstacles, and propose a learning model with abstain. Finally, we present a polynomial learning algorithm.

Original language	English
Title of host publication	Language and Automata Theory and Applications
Subtitle of host publication	8th International Conference, LATA 2014, Madrid, Spain, March 10-14, 2014. Proceedings
Publisher	Springer
Pages	490-502
Number of pages	13
Volume	8370
ISBN (Electronic)	978-3-319-04921-2
ISBN (Print)	978-3-319-04920-5
DOIs	https://doi.org/10.1007/978-3-319-04921-2_40
Publication status	Published - 2014

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10.1007/978-3-319-04921-2_40

Lawrence Lemay ET AL 2014 Learning Sequential Tree-to-Word TransducersAccepted author manuscript, 372 KB

http://dx.doi.org/10.1007/978-3-319-04921-2_40

Cite this

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title = "Learning Sequential Tree-to-Word Transducers",

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author = "Gr{\'e}goire Laurence and Aur{\'e}lien Lemay and Joachim Niehren and Slawek Staworko and Marc Tommasi",

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Learning Sequential Tree-to-Word Transducers. / Laurence, Grégoire; Lemay, Aurélien; Niehren, Joachim et al.
Language and Automata Theory and Applications: 8th International Conference, LATA 2014, Madrid, Spain, March 10-14, 2014. Proceedings. Vol. 8370 Springer, 2014. p. 490-502.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Learning Sequential Tree-to-Word Transducers

AU - Laurence, Grégoire

AU - Lemay, Aurélien

AU - Niehren, Joachim

AU - Staworko, Slawek

AU - Tommasi, Marc

PY - 2014

Y1 - 2014

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AB - We study the problem of learning sequential top-down tree-to-word transducers (stws). First, we present a Myhill-Nerode characterization of the corresponding class of sequential tree-to-word transformations ( TeX ). Next, we investigate what learning of stws means, identify fundamental obstacles, and propose a learning model with abstain. Finally, we present a polynomial learning algorithm.

U2 - 10.1007/978-3-319-04921-2_40

DO - 10.1007/978-3-319-04921-2_40

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VL - 8370

SP - 490

EP - 502

BT - Language and Automata Theory and Applications

PB - Springer

ER -

Learning Sequential Tree-to-Word Transducers

Abstract

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