-
1
-
-
84958264664
-
-
Software tensorflow. org
-
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al. 2015. TensorFlow: Large-scale machine learning on heterogeneous systems. Software available from tensorflow. org.
-
(2015)
TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems
-
-
Abadi, M.1
Agarwal, A.2
Barham, P.3
Brevdo, E.4
Chen, Z.5
Citro, C.6
Corrado, G.S.7
Davis, A.8
Dean, J.9
Devin, M.10
-
3
-
-
85083953689
-
Neural machine translation by jointly learning to align and translate
-
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015. Neural machine translation by jointly learning to align and translate. In Proceedings of ICLR.
-
(2015)
Proceedings of ICLR
-
-
Bahdanau, D.1
Cho, K.2
Bengio, Y.3
-
4
-
-
80053278031
-
Recognising textual entailment with logical inference
-
Johan Bos and Katja Markert. 2005. Recognising textual entailment with logical inference. In Proceedings of EMNLP.
-
(2005)
Proceedings of EMNLP
-
-
Bos, J.1
Markert, K.2
-
6
-
-
85021645849
-
A fast unified model for parsing and sentence understanding
-
Samuel R. Bowman, Jon Gauthier, Abhinav Rastogi, Raghav Gupta, Christopher D. Manning, and Christopher Potts. 2016. A fast unified model for parsing and sentence understanding. In Proceedings of ACL.
-
(2016)
Proceedings of ACL
-
-
Bowman, S.R.1
Gauthier, J.2
Rastogi, A.3
Gupta, R.4
Manning, C.D.5
Potts, C.6
-
8
-
-
85072834801
-
Long short-term memory-networks for machine reading
-
Jianpeng Cheng, Li Dong, and Mirella Lapata. 2016. Long short-term memory-networks for machine reading. In Proceedings of EMNLP.
-
(2016)
Proceedings of EMNLP
-
-
Cheng, J.1
Dong, L.2
Lapata, M.3
-
9
-
-
84859902208
-
Paraphrase identification as probabilistic quasi-synchronous recognition
-
Dipanjan Das and Noah A. Smith. 2009. Paraphrase identification as probabilistic quasi-synchronous recognition. In Proceedings of ACL-IJCNLP.
-
(2009)
Proceedings of ACL-IJCNLP
-
-
Das, D.1
Smith, N.A.2
-
10
-
-
80052250414
-
Adaptive subgradient methods for online learning and stochastic optimization
-
John Duchi, Elad Hazan, and Yoram Singer. 2011. Adaptive subgradient methods for online learning and stochastic optimization. The Journal of Machine Learning Research, 12:2121-2159.
-
(2011)
The Journal of Machine Learning Research
, vol.12
, pp. 2121-2159
-
-
Duchi, J.1
Hazan, E.2
Singer, Y.3
-
16
-
-
84937936034
-
Convolutional neural network architectures for matching natural language sentences
-
Baotian Hu, Zhengdong Lu, Hang Li, and Qingcai Chen. 2014. Convolutional neural network architectures for matching natural language sentences. In Advances in NIPS.
-
(2014)
Advances in NIPS
-
-
Hu, B.1
Lu, Z.2
Li, H.3
Chen, Q.4
-
19
-
-
0000494466
-
Handwritten digit recognition with a back-propagation network
-
Y. LeCun, B. Boser, J.S. Denker, D. Henderson, R.E. Howard, W. Hubbard, and L.D. Jackel. 1990. Handwritten digit recognition with a back-propagation network. In Advances in NIPS.
-
(1990)
Advances in NIPS
-
-
LeCun, Y.1
Boser, B.2
Denker, J.S.3
Henderson, D.4
Howard, R.E.5
Hubbard, W.6
Jackel, L.D.7
-
24
-
-
85072835395
-
Natural language inference by tree-based convolution and heuristic matching
-
Lili Mou, Men Rui, Ge Li, Yan Xu, Lu Zhang, Rui Yan, and Zhi Jin. 2015. Natural language inference by tree-based convolution and heuristic matching. In Proceedings of ACL (short papers).
-
(2015)
Proceedings of ACL (Short Papers)
-
-
Mou, L.1
Rui, M.2
Li, G.3
Xu, Y.4
Zhang, L.5
Yan, R.6
Jin, Z.7
-
27
-
-
84904163933
-
Dropout: A simple way to prevent neural networks from overfitting
-
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014. Dropout: A simple way to prevent neural networks from overfitting. The Journal of Machine Learning Research, 15(1):1929-1958.
-
(2014)
The Journal of Machine Learning Research
, vol.15
, Issue.1
, pp. 1929-1958
-
-
Srivastava, N.1
Hinton, G.2
Krizhevsky, A.3
Sutskever, I.4
Salakhutdinov, R.5
-
30
-
-
84994156970
-
Learning natural language inference with LSTM
-
Shuohang Wang and Jing Jiang. 2016. Learning natural language inference with LSTM. In Proceedings of NAACL.
-
(2016)
Proceedings of NAACL
-
-
Wang, S.1
Jiang, J.2
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