The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Multichannel Variable-Size Convolution for Sentence Classification
Open accessAbstract
We propose MVCNN, a convolution neural network (CNN) architecture for sentence classification.It (i) combines diverse versions of pretrained word embeddings and (ii) extracts features of multigranular phrases with variable-size convolution filters.We also show that pretraining MVCNN is critical for good performance.MVCNN achieves state-of-the-art performance on four tasks: on small-scale binary, small-scale multi-class and largescale Twitter sentiment prediction and on subjectivity classification.
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Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
Efficient Estimation of Word Representations in Vector Space
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1301.3781 · Cited by 26,568
Improving neural networks by preventing co-adaptation of feature detectors
Hinton, G. E., Srivastava, N., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. R. (2012) · arXiv · doi:10.48550/arxiv.1207.0580 · Cited by 6,382
Recurrent neural network based language model
Mikolov, T., Karafiát, M., Burget, L., Černocký, J., & Khudanpur, S. (2010) · Interspeech 2010 · doi:10.21437/interspeech.2010-343 · Cited by 5,390
A unified architecture for natural language processing: deep neural networks with multitask learning
Collobert, R., & Weston, J. (2008) · Proceedings of the 25th international conference on Machine learning - ICML '08 · doi:10.1145/1390156.1390177 · Cited by 5,058
Cited by
Recent advances in convolutional neural networks
Gu, J., Wang, Z., Kuen, J., Ma, L., Shahroudy, A., Shuai, B., Liu, T., Wang, X., Wang, G., Cai, J., et al. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2017.10.013 · Cited by 6,576
A Survey of Optimization Methods From a Machine Learning Perspective
Sun, S., Cao, Z., Zhu, H., & Zhao, J. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2019.2950779 · Cited by 789
Sadr, H., Pedram, M. M., & Teshnehlab, M. (2019) · Neural Processing Letters · doi:10.1007/s11063-019-10049-1 · Cited by 82
Metadata
- Authors
- Yin, W., & Schütze, H.
- Venue
- Proceedings of the Nineteenth Conference on Computational Natural Language Learning
- Published
- 2015
- Pages
- 204-214
- OpenAlex
- W2251908874
- Cited by
- 162
- References
- 5
- FWCI
- 10.23
- Type
- conference paper
- Language
- en
- Open access
- gold
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