-
1
-
-
0036475447
-
A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking
-
2002
-
M. Sanjeev Arulampalam, Simon Maskell, Neil Gordon, and Tim Clapp. 2002. A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking. IEEE Transactions on Signal Processing 50, 2 (2002), 174-188.
-
(2002)
IEEE Transactions on Signal Processing
, vol.50
, Issue.2
, pp. 174-188
-
-
Sanjeev Arulampalam, M.1
Maskell, S.2
Gordon, N.3
Clapp, T.4
-
2
-
-
0032626544
-
Improved particle filter for nonlinear problems
-
IET
-
James Carpenter, Peter Clifford, and Paul Fearnhead. 1999. Improved particle filter for nonlinear problems. In IEEE Proceedings on Radar, Sonar and Navigation 146. IET, 2-7.
-
(1999)
IEEE Proceedings on Radar, Sonar and Navigation
, vol.146
, pp. 2-7
-
-
Carpenter, J.1
Clifford, P.2
Fearnhead, P.3
-
3
-
-
0031142667
-
An iterative pruning algorithm for feedforward neural networks
-
1997
-
Giovanna Castellano, Anna Maria Fanelli, and Marcello Pelillo. 1997. An iterative pruning algorithm for feedforward neural networks. IEEE Transactions on Neural Networks 8, 3 (1997), 519-531.
-
(1997)
IEEE Transactions on Neural Networks
, vol.8
, Issue.3
, pp. 519-531
-
-
Castellano, G.1
Fanelli, A.M.2
Pelillo, M.3
-
5
-
-
84944081816
-
-
2014. Arxiv Preprint Arxiv:1410.0759
-
Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, and Evan Shelhamer. 2014. Cudnn: Efficient primitives for deep learning. Arxiv Preprint Arxiv:1410.0759 (2014).
-
(2014)
Cudnn: Efficient Primitives for Deep Learning
-
-
Chetlur, S.1
Woolley, C.2
Vandermersch, P.3
Cohen, J.4
Tran, J.5
Catanzaro, B.6
Shelhamer, E.7
-
11
-
-
85032751458
-
Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups
-
2012
-
Geoffrey Hinton, Li Deng, Dong Yu, George E. Dahl, Abdel-rahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Tara N. Sainath, and others. 2012. Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. IEEE Signal Processing Magazine 29, 6 (2012), 82-97.
-
(2012)
IEEE Signal Processing Magazine
, vol.29
, Issue.6
, pp. 82-97
-
-
Hinton, G.1
Deng, L.2
Yu, D.3
Dahl, G.E.4
Mohamed, A.-R.5
Jaitly, N.6
Senior, A.7
Vanhoucke, V.8
Nguyen, P.9
Sainath, T.N.10
-
17
-
-
0032203257
-
Gradient-based learning applied to document recognition
-
1998
-
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner. 1998. Gradient-based learning applied to document recognition. Proceedings of the IEEE 86, 11 (1998), 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
-
18
-
-
84892589545
-
Fight sample degeneracy and impoverishment in particle filters: A review of intelligent approaches
-
2014
-
Tiancheng Li, Shudong Sun, Tariq Pervez Sattar, and Juan Manuel Corchado. 2014. Fight sample degeneracy and impoverishment in particle filters: A review of intelligent approaches. Expert Systems with Applications 41, 8 (2014), 3944-3954.
-
(2014)
Expert Systems with Applications
, vol.41
, Issue.8
, pp. 3944-3954
-
-
Li, T.1
Sun, S.2
Sattar, T.P.3
Corchado, J.M.4
-
20
-
-
61949168057
-
Parameter estimation of in silico biological pathways with particle filtering towards a petascale computing
-
Kazuyuki Nakamura, Ryo Yoshida, Masao Nagasaki, Satoru Miyano, and Tomoyuki Higuchi. 2009. Parameter estimation of in silico biological pathways with particle filtering towards a petascale computing. In Proceedings of the Pacific Symposium on Biocomputing 14. 227-238.
-
(2009)
Proceedings of the Pacific Symposium on Biocomputing
, vol.14
, pp. 227-238
-
-
Nakamura, K.1
Yoshida, R.2
Nagasaki, M.3
Miyano, S.4
Higuchi, T.5
-
21
-
-
84865114495
-
Reading digits in natural images with unsupervised feature learning
-
Y. Netzer, T. Wang, A. Coates, A. Bissacco, B. Wu, and A. Y. Ng. 2011. Reading digits in natural images with unsupervised feature learning. In NIPS Workshop on Deep Learning and Unsupervised Feature Learning 2011.
-
(2011)
NIPS Workshop on Deep Learning and Unsupervised Feature Learning 2011
-
-
Netzer, Y.1
Wang, T.2
Coates, A.3
Bissacco, A.4
Wu, B.5
Ng, A.Y.6
-
22
-
-
0037428077
-
An adaptive color-based particle filter
-
2003
-
Katja Nummiaro, Esther Koller-Meier, and Luc Van Gool. 2003. An adaptive color-based particle filter. Image and Vision Computing 21, 1 (2003), 99-110.
-
(2003)
Image and Vision Computing
, vol.21
, Issue.1
, pp. 99-110
-
-
Nummiaro, K.1
Koller-Meier, E.2
Van Gool, L.3
-
23
-
-
84961358915
-
Channel-level acceleration of deep face representations
-
2015
-
Adam Polyak and Lior Wolf. 2015. Channel-level acceleration of deep face representations. IEEE Access 3 (2015), 2163-2175.
-
(2015)
IEEE Access
, vol.3
, pp. 2163-2175
-
-
Polyak, A.1
Wolf, L.2
-
24
-
-
0027662338
-
Pruning algorithms-a survey
-
1993
-
Russell Reed. 1993. Pruning algorithms-a survey. IEEE Transactions on Neural Networks 4, 5 (1993), 740-747.
-
(1993)
IEEE Transactions on Neural Networks
, vol.4
, Issue.5
, pp. 740-747
-
-
Reed, R.1
-
27
-
-
84904163933
-
Dropout: A simple way to prevent neural networks from overfitting
-
2014
-
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014. Dropout: A simple way to prevent neural networks from overfitting. Journal of Machine Learning Research 15, 1 (2014), 1929-1958.
-
(2014)
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
-
28
-
-
21744462897
-
Pruning backpropagation neural networks using modern stochastic optimisation techniques
-
1997
-
Slawomir W. Stepniewski and Andy J. Keane. 1997. Pruning backpropagation neural networks using modern stochastic optimisation techniques. Neural Computing & Applications 5, 2 (1997), 76-98.
-
(1997)
Neural Computing & Applications
, vol.5
, Issue.2
, pp. 76-98
-
-
Stepniewski, S.W.1
Keane, A.J.2
-
31
-
-
84893343292
-
Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude
-
2012
-
Tijmen Tieleman and Geoffrey Hinton. 2012. Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude. COURSERA: Neural Networks for Machine Learning 4 (2012), 2.
-
(2012)
COURSERA: Neural Networks for Machine Learning
, vol.4
, pp. 2
-
-
Tieleman, T.1
Hinton, G.2
-
33
-
-
84897550107
-
Regularization of neural networks using dropconnect
-
Li Wan, Matthew Zeiler, Sixin Zhang, Yann L. Cun, and Rob Fergus. 2013. Regularization of neural networks using dropconnect. In Proceedings of the 30th International Conference on Machine Learning (ICML-13). 1058-1066.
-
(2013)
Proceedings of the 30th International Conference on Machine Learning (ICML-13)
, pp. 1058-1066
-
-
Wan, L.1
Zeiler, M.2
Zhang, S.3
Cun, Y.L.4
Fergus, R.5
|