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Log-Linear Weight Optimization Using Discriminative Ridge Regression Method in Statistical Machine Translation

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Log-Linear Weight Optimization Using Discriminative Ridge Regression Method in Statistical Machine Translation

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Chinea-Ríos, M.; Sanchis Trilles, G.; Casacuberta Nolla, F. (2017). Log-Linear Weight Optimization Using Discriminative Ridge Regression Method in Statistical Machine Translation. Lecture Notes in Computer Science. 10255:32-41. https://doi.org/10.1007/978-3-319-58838-4_4

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/103609

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Metadatos del ítem

Título: Log-Linear Weight Optimization Using Discriminative Ridge Regression Method in Statistical Machine Translation
Autor: Chinea-Ríos, Mara Sanchis Trilles, Germán Casacuberta Nolla, Francisco
Entidad UPV: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Fecha difusión:
Resumen:
[EN] We present a simple and reliable method for estimating the log-linear weights of a state-of-the-art machine translation system, which takes advantage of the method known as discriminative ridge regression (DRR). Since ...[+]
Palabras clave: Statistical machine translation , Log-linear model , Discriminative ridge regression
Derechos de uso: Reserva de todos los derechos
Fuente:
Lecture Notes in Computer Science. (issn: 0302-9743 )
DOI: 10.1007/978-3-319-58838-4_4
Editorial:
Springer-Verlag
Versión del editor: https://doi.org/10.1007/978-3-319-58838-4_4
Título del congreso: 8th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2017)
Lugar del congreso: Faro, Portugal
Fecha congreso: June 20-23,2017
Código del Proyecto:
info:eu-repo/grantAgreement/GVA//PROMETEOII%2F2014%2F030/ES/ Adaptive learning and multimodality in machine translation and text transcription/
Agradecimientos:
The research leading to these results has received funding fromthe Generalitat Valenciana under grant PROMETEOII/2014/030 and the FPI (2014) grant by Universitat Politècnica de València.
Tipo: Artículo Comunicación en congreso

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