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LREC 2016main

LibN3L:A Lightweight Package for Neural NLP

Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)

DOI:10.63317/3nqgpgnhe8bz

Abstract

We present a light-weight machine learning tool for NLP research. The package supports operations on both discrete and dense vectors, facilitating implementation of linear models as well as neural models. It provides several basic layers which mainly aims for single-layer linear and non-linear transformations. By using these layers, we can conveniently implement linear models and simple neural models. Besides, this package also integrates several complex layers by composing those basic layers, such as RNN, Attention Pooling, LSTM and gated RNN. Those complex layers can be used to implement deep neural models directly.

Details

Paper ID
lrec2016-main-034
Pages
pp. 225-229
BibKey
zhang-etal-2016-libn3l
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
978-2-9517408-9-1
Conference
Tenth International Conference on Language Resources and Evaluation
Location
Portorož, Slovenia
Date
23 May 2016 28 May 2016

Authors

  • MZ

    Meishan Zhang

  • JY

    Jie Yang

  • ZT

    Zhiyang Teng

  • YZ

    Yue Zhang

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