End-to-End Neural Text Classification for Tibetan-Reference-Cited by-同舟云学术

End-to-End Neural Text Classification for Tibetan

Published:2017 Issue: Volume: Page:472-480
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Qun Nuo,Li Xing,Qiu Xipeng,Huang Xuanjing

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-69005-6_39

Reference17 articles.

1. Cao, H., Jia, H.: Tibetan text classification based on the feature of position weight. In: International Conference on Asian Language Processing (IALP), pp. 220–223. IEEE (2013)

2. Chung, J., Gulcehre, C., Cho, K., Bengio, Y.: Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555 (2014)

3. Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., Kuksa, P.: Natural language processing (almost) from scratch. J. Mach. Learn. Res. 12, 2493–2537 (2011)

4. Duchi, J., Hazan, E., Singer, Y.: Adaptive subgradient methods for online learning and stochastic optimization. J. Mach. Learn. Res. 12, 2121–2159 (2011)

5. Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735–1780 (1997)

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