Fetching the paper…
Reading the bibliography…
With the rapid development in deep learning, deep neural networks have been widely adopted in many real-life natural language applications.
Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
Earlier work this paper cites.
Fast exact inference with a factored model for natural language parsing
Dan Klein and Christopher D Manning. 2003 · 2003
Earlier work this paper cites.
Using tf-idf to determine word relevance in document queries
Juan Ramos et al. 2003 · 2003
Earlier work this paper cites.
A note on the group lasso and a sparse group lasso
Jerome Friedman, Trevor Hastie, and Robert Tibshirani. 2010 · 2010
Earlier work this paper cites.
What is left to be understood in atis?
Gokhan Tur, Dilek Hakkani-Tür, and Larry Heck. 2010 · 2010
Earlier work this paper cites.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling. 2013 · 2013
Earlier work this paper cites.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
Earlier work this paper cites.
Fast dropout training
Sida Wang and Christopher Manning. 2013 · 2013
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
Earlier work this paper cites.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
Earlier work this paper cites.
TensorFlow: Large-scale machine learning on heterogeneous systems
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dandelion Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng. 2015 · 2015
Earlier work this paper cites.
A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
Earlier work this paper cites.
Sparse overcomplete word vector representations
Manaal Faruqui, Yulia Tsvetkov, Dani Yogatama, Chris Dyer, and Noah A. Smith. 2015 · 2015
Cited alongside, same era.
Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding
Song Han, Huizi Mao, and William J Dally. 2015 · 2015
Cited alongside, same era.
Variational dropout and the local reparameterization trick
Diederik P Kingma, Tim Salimans, and Max Welling. 2015 · 2015
Cited alongside, same era.
A simple way to initialize recurrent networks of rectified linear units
Quoc V. Le, Navdeep Jaitly, and Geoffrey E. Hinton. 2015 · 2015
Cited alongside, same era.
Dbpedia–a large-scale, multilingual knowledge base extracted from wikipedia
Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick Van Kleef, Sören Auer, et al. 2015 · 2015
Cited alongside, same era.
Enhanced LSTM for natural language inference
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Si Wei, Hui Jiang, and Diana Inkpen. 2017 · 2017
Later among the works it cites.
Quantized neural networks: Training neural networks with low precision weights and activations
Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, and Yoshua Bengio. 2017 · 2017
Later among the works it cites.
Fully character-level neural machine translation without explicit segmentation
Jason Lee, Kyunghyun Cho, and Thomas Hofmann. 2017 · 2017
Later among the works it cites.
Bayesian compression for deep learning
Christos Louizos, Karen Ullrich, and Max Welling. 2017 · 2017
Later among the works it cites.
Variational dropout sparsifies deep neural networks
Dmitry Molchanov, Arsenii Ashukha, and Dmitry P. Vetrov. 2017 · 2017
Later among the works it cites.
Structured bayesian pruning via log-normal multiplicative noise
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Sparse convolutional neural networks
Baoyuan Liu, Min Wang, Hassan Foroosh, Marshall Tappen, and Marianna Pensky. 2015 · 2015
Cited alongside, same era.
Effective approaches to attention-based neural machine translation
Thang Luong, Hieu Pham, and Christopher D. Manning. 2015 · 2015
Cited alongside, same era.
Learning word representations with hierarchical sparse coding
Dani Yogatama, Manaal Faruqui, Chris Dyer, and Noah A. Smith. 2015 · 2015
Cited alongside, same era.
Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
Cited alongside, same era.
Character-based neural machine translation
Marta R. Costa-Jussà and José A. R. Fonollosa. 2016 · 2016
Cited alongside, same era.
Character-aware neural language models
Yoon Kim, Yacine Jernite, David Sontag, and Alexander M Rush. 2016 · 2016
Cited alongside, same era.
Attention-based recurrent neural network models for joint intent detection and slot filling
Bing Liu and Ian Lane. 2016 · 2016
Cited alongside, same era.
Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha, and Dmitry P Vetrov. 2017 · 2017
Later among the works it cites.
Compressing recurrent neural network with tensor train
Andros Tjandra, Sakriani Sakti, and Satoshi Nakamura. 2017 · 2017
Later among the works it cites.
Bayesian compression for natural language processing
Nadezhda Chirkova, Ekaterina Lobacheva, and Dmitry Vetrov. 2018 · 2018
Later among the works it cites.
Alice Coucke, Alaa Saade, Adrien Ball, Théodore Bluche, Alexandre Caulier, David Leroy, Clément Doumouro, Thibault Gisselbrecht, Francesco Caltagirone, Thibaut Lavril, Maël Primet, and Joseph Dureau. 2018 · 2018
Later among the works it cites.
Slot-gated modeling for joint slot filling and intent prediction
Chih-Wen Goo, Guang Gao, Yun-Kai Hsu, Chih-Li Huo, Tsung-Chieh Chen, Keng-Wei Hsu, and Yun-Nung Chen. 2018 · 2018
Later among the works it cites.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel R. Bowman. 2018 · 2018
Later among the works it cites.
Learning structured sparsity in deep neural networks
Wei Wen, Chunpeng Wu, Yandan Wang, Yiran Chen, and Hai Li. 2016 · 2082
Closest in time.