-
3
-
-
84908188761
-
-
arXiv preprint
-
Calandra, R., Peters, J., Rasmussen, C. E., and Deisenroth, M. P. (2014). Manifold gaussian processes for regression. arXiv preprint arXiv:1402.5876.
-
(2014)
Manifold Gaussian Processes for Regression
-
-
Calandra, R.1
Peters, J.2
Rasmussen, C.E.3
Deisenroth, M.P.4
-
6
-
-
85032751458
-
Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups
-
Hinton, G. E., Deng, L., Yu, D., Dahl, G. E., rahman Mohamed, A., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T. N., and Kingsbury, B. (2012). Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. IEEE Signal Process. Mag., 29(6):82–97.
-
(2012)
IEEE Signal Process. Mag.
, vol.29
, Issue.6
, pp. 82-97
-
-
Hinton, G.E.1
Deng, L.2
Yu, D.3
Dahl, G.E.4
rahman Mohamed, A.5
Jaitly, N.6
Senior, A.7
Vanhoucke, V.8
Nguyen, P.9
Sainath, T.N.10
Kingsbury, B.11
-
7
-
-
33745805403
-
A fast learning algorithm for deep belief nets
-
Hinton, G. E., Osindero, S., and Teh, Y. W. (2006). A fast learning algorithm for deep belief nets. Neural Computation, 18(7):1527–1554.
-
(2006)
Neural Computation
, vol.18
, Issue.7
, pp. 1527-1554
-
-
Hinton, G.E.1
Osindero, S.2
Teh, Y.W.3
-
8
-
-
84949813690
-
Scalable gaussian process regression using deep neural networks
-
AAAI Press
-
Huang, W., Zhao, D., Sun, F., Liu, H., and Chang, E. (2015). Scalable gaussian process regression using deep neural networks. In Proceedings of the 24th International Conference on Artificial Intelligence, pages 3576–3582. AAAI Press.
-
(2015)
Proceedings of the 24th International Conference on Artificial Intelligence
, pp. 3576-3582
-
-
Huang, W.1
Zhao, D.2
Sun, F.3
Liu, H.4
Chang, E.5
-
9
-
-
84913555165
-
-
arXiv preprint
-
Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., and Darrell, T. (2014). Caffe: Convolutional architecture for fast feature embedding. arXiv preprint arXiv:1408.5093.
-
(2014)
Caffe: Convolutional Architecture for Fast Feature Embedding
-
-
Jia, Y.1
Shelhamer, E.2
Donahue, J.3
Karayev, S.4
Long, J.5
Girshick, R.6
Guadarrama, S.7
Darrell, T.8
-
10
-
-
84952349298
-
Unifying visual-semantic embeddings with multimodal neural language models
-
Kiros, R., Salakhutdinov, R., and Zemel, R. (2014). Unifying visual-semantic embeddings with multimodal neural language models. TACL.
-
(2014)
TACL
-
-
Kiros, R.1
Salakhutdinov, R.2
Zemel, R.3
-
12
-
-
84898989411
-
Fastfood-computing hilbert space expansions in loglinear time
-
Le, Q., Sarlos, T., and Smola, A. (2013). Fastfood-computing Hilbert space expansions in loglinear time. In Proceedings of the 30th International Conference on Machine Learning, pages 244–252.
-
(2013)
Proceedings of the 30th International Conference on Machine Learning
, pp. 244-252
-
-
Le, Q.1
Sarlos, T.2
Smola, A.3
-
13
-
-
0032203257
-
Gradient-based learning applied to document recognition
-
LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11):2278–2324.
-
(1998)
Proceedings of the IEEE
, vol.86
, Issue.11
, pp. 2278-2324
-
-
LeCun, Y.1
Bottou, L.2
Bengio, Y.3
Haffner, P.4
-
14
-
-
84965136294
-
Automatic construction and Natural-Language description of nonparametric regression models
-
Lloyd, J. R., Duvenaud, D., Grosse, R., Tenenbaum, J. B., and Ghahramani, Z. (2014). Automatic construction and Natural-Language description of nonparametric regression models. In Association for the Advancement of Artificial Intelligence (AAAI).
-
(2014)
Association for the Advancement of Artificial Intelligence (AAAI)
-
-
Lloyd, J.R.1
Duvenaud, D.2
Grosse, R.3
Tenenbaum, J.B.4
Ghahramani, Z.5
-
15
-
-
0003319647
-
Introduction to gaussian processes
-
Bishop, C. M., editor, chapter 11, Springer-Verlag
-
MacKay, D. J. (1998). Introduction to Gaussian processes. In Bishop, C. M., editor, Neural Networks and Machine Learning, chapter 11, pages 133–165. Springer-Verlag.
-
(1998)
Neural Networks and Machine Learning
, pp. 133-165
-
-
MacKay, D.J.1
-
16
-
-
33845518144
-
Universal kernels
-
Micchelli, C. A., Xu, Y., and Zhang, H. (2006). Universal kernels. The Journal of Machine Learning Research, 7:2651–2667.
-
(2006)
The Journal of Machine Learning Research
, vol.7
, pp. 2651-2667
-
-
Micchelli, C.A.1
Xu, Y.2
Zhang, H.3
-
23
-
-
84970022032
-
Scalable bayesian optimization using deep neural networks
-
Snoek, J., Rippel, O., Swersky, K., Kiros, R., Satish, N., Sundaram, N., Patwary, M., Ali, M., and Adams, R. P. (2015). Scalable bayesian optimization using deep neural networks. In International Conference on Machine Learning.
-
(2015)
International Conference on Machine Learning
-
-
Snoek, J.1
Rippel, O.2
Swersky, K.3
Kiros, R.4
Satish, N.5
Sundaram, N.6
Patwary, M.7
Ali, M.8
Adams, R.P.9
-
24
-
-
85162476102
-
Dynamic pooling and unfolding recursive autoencoders for paraphrase detection
-
Socher, R., Huang, E., Pennington, J., Ng, A., and Manning, C. (2011). Dynamic pooling and unfolding recursive autoencoders for paraphrase detection. In Advances in Neural Information Processing Systems 24, pages 801–809.
-
(2011)
Advances in Neural Information Processing Systems
, vol.24
, pp. 801-809
-
-
Socher, R.1
Huang, E.2
Pennington, J.3
Ng, A.4
Manning, C.5
-
27
-
-
85014056051
-
-
Technical Report, Carnegie Mellon University
-
Wilson, A. G., Dann, C., and Nickisch, H. (2015). Thoughts on massively scalable Gaussian processes. Technical Report, Carnegie Mellon University. http://www.cs.cmu.edu/~andrewgw/msgp.html.
-
(2015)
Thoughts on Massively Scalable Gaussian Processes
-
-
Wilson, A.G.1
Dann, C.2
Nickisch, H.3
-
30
-
-
84970002232
-
Show, attend and tell: Neural image caption generation with visual attention
-
Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A. C., Salakhutdinov, R., Zemel, R. S., and Bengio, Y. (2015). Show, attend and tell: Neural image caption generation with visual attention. ICML.
-
(2015)
ICML
-
-
Xu, K.1
Ba, J.2
Kiros, R.3
Cho, K.4
Courville, A.C.5
Salakhutdinov, R.6
Zemel, R.S.7
Bengio, Y.8
-
31
-
-
84965146939
-
-
arXiv preprint
-
Yang, Z., Moczulski, M., Denil, M., de Freitas, N., Smola, A., Song, L., and Wang, Z. (2014). Deep fried convnets. arXiv preprint arXiv:1412.7149.
-
(2014)
Deep Fried Convnets
-
-
Yang, Z.1
Moczulski, M.2
Denil, M.3
de Freitas, N.4
Smola, A.5
Song, L.6
Wang, Z.7
-
32
-
-
84969544477
-
A la carte - learning fast kernels
-
Yang, Z., Smola, A. J., Song, L., and Wilson, A. G. (2015). A la carte - learning fast kernels. Artificial Intelligence and Statistics.
-
(2015)
Artificial Intelligence and Statistics
-
-
Yang, Z.1
Smola, A.J.2
Song, L.3
Wilson, A.G.4
|