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Fallback Variable History NNLMs: Efficient NNLMs by precomputation and stochastic training

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Fallback Variable History NNLMs: Efficient NNLMs by precomputation and stochastic training

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Zamora Martínez, FJ.; España Boquera, S.; Castro-Bleda, MJ.; Palacios Corella (2018). Fallback Variable History NNLMs: Efficient NNLMs by precomputation and stochastic training. PLoS ONE. 13(7). https://doi.org/10.1371/journal.pone.0200884

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/126934

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Title: Fallback Variable History NNLMs: Efficient NNLMs by precomputation and stochastic training
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
[EN] This paper presents a new method to reduce the computational cost when using Neural Networks as Language Models, during recognition, in some particular scenarios. It is based on a Neural Network that considers input ...[+]
Copyrigths: Reconocimiento (by)
Source:
PLoS ONE. (issn: 1932-6203 )
DOI: 10.1371/journal.pone.0200884
Publisher:
Public Library of Science
Publisher version: http://doi.org/10.1371/journal.pone.0200884
Thanks:
This work was partially supported by the Spanish MINECO and FEDER founds under project TIN2017-85854-C4-2-R (to MJCB). The funders had no role in study design, data collection and analysis, decision to publish, or preparation ...[+]
Type: Artículo

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