@inproceedings{zhang-etal-2016-libn3l,
title = "{L}ib{N}3{L}:A Lightweight Package for Neural {NLP}",
author = "Zhang, Meishan and
Yang, Jie and
Teng, Zhiyang and
Zhang, Yue",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Goggi, Sara and
Grobelnik, Marko and
Maegaard, Bente and
Mariani, Joseph and
Mazo, Helene and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
month = may,
year = "2016",
address = "Portoro{\v{z}}, Slovenia",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L16-1034",
pages = "225--229",
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.",
}
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%0 Conference Proceedings
%T LibN3L:A Lightweight Package for Neural NLP
%A Zhang, Meishan
%A Yang, Jie
%A Teng, Zhiyang
%A Zhang, Yue
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Grobelnik, Marko
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Helene
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)
%D 2016
%8 May
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F zhang-etal-2016-libn3l
%X 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.
%U https://aclanthology.org/L16-1034
%P 225-229
Markdown (Informal)
[LibN3L:A Lightweight Package for Neural NLP](https://aclanthology.org/L16-1034) (Zhang et al., LREC 2016)
ACL
- Meishan Zhang, Jie Yang, Zhiyang Teng, and Yue Zhang. 2016. LibN3L:A Lightweight Package for Neural NLP. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 225–229, Portorož, Slovenia. European Language Resources Association (ELRA).