Compressing Word Embeddings-Reference-Cited by-同舟云学术

Compressing Word Embeddings

Published:2016 Issue: Volume: Page:413-422
ISSN:0302-9743
Container-title:Neural Information Processing
language:
Short-container-title:

Author:

Andrews Martin

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-46681-1_50

Reference20 articles.

1. Murphy, B., Talukdar, P.P., Mitchell, T.: Learning effective and interpretable semantic models using non-negative sparse embedding. In: International Conference on Computational Linguistics (COLING 2012), Mumbai, India (2012). http://aclweb.org/anthology/C/C12/C12-1118.pdf

2. Griffiths, T.L., Steyvers, M., Tenenbaum, J.B.: Topics in semantic representation. Psychol. Rev. 114(2), 211 (2007)

3. Vinson, D.P., Vigliocco, G.: Semantic feature production norms for a large set of objects and events. Behav. Res. Methods 40(1), 183–190 (2008)

4. Pennington, J., Socher, R., Manning, C.D.: Glove: global vectors for word representation. Proceedings of the Empiricial Methods in Natural Language Processing (EMNLP 2014) 12, 1532–1543 (2014)

5. Lloyd, S.: Least squares quantization in PCM. IEEE Trans. Inf. Theory 28(2), 129–137 (2006)

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