-
1
-
-
0000396062
-
Natural gradient works efficiently in learning
-
Amari, Shun-Ichi. Natural gradient works efficiently in learning. Neural Computation, 10(2):251-276, 1998.
-
(1998)
Neural Computation
, vol.10
, Issue.2
, pp. 251-276
-
-
Amari, S.-I.1
-
4
-
-
84877799221
-
Enhanced gradient for training restricted Boltzmann machines
-
Cho, K., Raiko, t., and Ilin, A. Enhanced gradient for training restricted Boltzmann machines. Neural Computation, 25:805-813, 2013.
-
(2013)
Neural Computation
, vol.25
, pp. 805-813
-
-
Cho, K.1
Raiko, T.2
Ilin, A.3
-
5
-
-
84877760312
-
Large scale distributed deep networks
-
Dean, J., Corrado, G. S., Monga, R., Chen, K., Devin, M., Le, Q. V., Mao, M. Z., Ranzato, M., Senior, A., Tucker, P., Yang, K., and Ng, A. Y. Large scale distributed deep networks. In Neural Information Processing Systems, 2012.
-
(2012)
Neural Information Processing Systems
-
-
Dean, J.1
Corrado, G.S.2
Monga, R.3
Chen, K.4
Devin, M.5
Le, Q.V.6
Mao, M.Z.7
Ranzato, M.8
Senior, A.9
Tucker, P.10
Yang, K.11
Ng, A.Y.12
-
7
-
-
84965130201
-
-
arXiv. 1507.00210
-
Desjardins, G., Simonyan, K., Pascanu, R., and Kavukcuoglu, K. Natural neural networks. arXiv. 1507.00210, 2015.
-
(2015)
Natural Neural Networks
-
-
Desjardins, G.1
Simonyan, K.2
Pascanu, R.3
Kavukcuoglu, K.4
-
8
-
-
80052250414
-
Adaptive subgradient methods for online learning and stochastic optimization
-
Duchi, J., Hazan, E., and Singer, Y. Adaptive subgradient methods for online learning and stochastic optimization. Journal of Machine Learning Research, 12:2121-2159, 2011.
-
(2011)
Journal of Machine Learning Research
, vol.12
, pp. 2121-2159
-
-
Duchi, J.1
Hazan, E.2
Singer, Y.3
-
10
-
-
0034167148
-
On "natural" learning and pruning in multilayered perceptrons
-
Heskes, Tom. On "natural" learning and pruning in multilayered perceptrons. Neural Computation, 12(4):881-901, 2000.
-
(2000)
Neural Computation
, vol.12
, Issue.4
, pp. 881-901
-
-
Heskes, T.1
-
12
-
-
84969584486
-
Batch normalization: Accelerating deep network training by reducing internal covariate shift
-
Ioffe, S. and Szegedy, C. Batch normalization: accelerating deep network training by reducing internal covariate shift. In International Conference on Machine Learning, 2015.
-
(2015)
International Conference on Machine Learning
-
-
Ioffe, S.1
Szegedy, C.2
-
16
-
-
85162000799
-
Topmoumoute online natural gradient algorithm
-
MIT Press
-
Le Roux, Nicolas, Manzagol, Pierre-antoine, and Bengio, Yoshua. Topmoumoute online natural gradient algorithm. In Advances in Neural Information Processing Systems 20, pp. 849-856. MIT Press, 2008.
-
(2008)
Advances in Neural Information Processing Systems
, vol.20
, pp. 849-856
-
-
Roux, N.1
Manzagol, P.-A.2
Bengio, Y.3
-
17
-
-
0000359337
-
Backpropagation applied to handwritten zip code recognition
-
LeCun, Y, Boser, B., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W., and Jackel, L. D. Backpropagation applied to handwritten zip code recognition. Neural Computation, 1:541-551, 1989.
-
(1989)
Neural Computation
, vol.1
, pp. 541-551
-
-
LeCun, Y.1
Boser, B.2
Denker, J.S.3
Henderson, D.4
Howard, R.E.5
Hubbard, W.6
Jackel, L.D.7
-
18
-
-
0001857994
-
Efficient backprop
-
LeCun, Y, Bottou, L., Orr, G., and Müller, K. Efficient backprop. Neural networks: Tricks of the trade, pp. 546-546, 1998.
-
(1998)
Neural Networks: Tricks of the Trade
, pp. 546
-
-
LeCun, Y.1
Bottou, L.2
Orr, G.3
Müller, K.4
-
22
-
-
78149337911
-
CUDAMat: A CUDA-based matrix class for Python
-
University of Toronto
-
Mnih, V. CUDAMat: A CUDA-based matrix class for Python. Technical Report 004, University of Toronto, 2009.
-
(2009)
Technical Report 004
-
-
Mnih, V.1
-
23
-
-
0001362410
-
The Levenberg-Marquardt algorithm: Implementation and theory
-
Moré, J. J. The Levenberg-Marquardt algorithm: implementation and theory. Numerical analysis, pp. 105-116, 1978.
-
(1978)
Numerical Analysis
, pp. 105-116
-
-
Moré, J.J.1
-
24
-
-
84865114495
-
Reading digits in natural images with unsupervised feature learning
-
Netzer, Y., Wang, T., Coates, A., Bissacco, A., Wu, B., and Ng, A. Y. Reading digits in natural images with unsupervised feature learning. In Neural Information Processing Systems Deep Learning and Unsupervised Feature Learning Workshop, 2011.
-
(2011)
Neural Information Processing Systems Deep Learning and Unsupervised Feature Learning Workshop
-
-
Netzer, Y.1
Wang, T.2
Coates, A.3
Bissacco, A.4
Wu, B.5
Ng, A.Y.6
-
26
-
-
84999035113
-
Riemannian metrics for neural networks I: Feedforward networks
-
Ollivier, Y. Riemannian metrics for neural networks I: feedforward networks. Information and Inference, 4(2):108-153, 2015.
-
(2015)
Information and Inference
, vol.4
, Issue.2
, pp. 108-153
-
-
Ollivier, Y.1
-
28
-
-
84937871648
-
-
arXiv: 1405.4604
-
Pascanu, R., Dauphin, Y. N., Ganguli, S., and Bengio, Y. On the saddle point problem for non-convex optimization. arXiv: 1405.4604, 2014.
-
(2014)
On the Saddle Point Problem for Non-convex Optimization
-
-
Pascanu, R.1
Dauphin, Y.N.2
Ganguli, S.3
Bengio, Y.4
-
31
-
-
77955989954
-
Modeling pixel means and covariances using factorized third-order Boltzmann machines
-
Ranzato, M. and Hinton, G. E. Modeling pixel means and covariances using factorized third-order Boltzmann machines. In Computer Vision and Pattern Recognition, 2010.
-
(2010)
Computer Vision and Pattern Recognition
-
-
Ranzato, M.1
Hinton, G.E.2
-
32
-
-
0036631778
-
Fast curvature matrix-vector products for second-order gradient descent
-
Schraudolph, Nicol N. Fast curvature matrix-vector products for second-order gradient descent. Neural Computation, 14, 2002.
-
(2002)
Neural Computation
, pp. 14
-
-
Schraudolph, N.N.1
-
38
-
-
77952681438
-
A tutorial on stochastic approximation algorithms for training restricted Boltzmann machines and deep belief nets
-
Jan.
-
Swersky, K., Chen, Bo, Marlin, B., and de Freitas, N. A tutorial on stochastic approximation algorithms for training restricted Boltzmann machines and deep belief nets. In Information Theory and Applications Workshop (ITA), 2010, pp. 1-10, Jan 2010.
-
(2010)
Information Theory and Applications Workshop (ITA), 2010
, pp. 1-10
-
-
Swersky, K.1
Chen, B.2
Marlin, B.3
Freitas, N.4
-
40
-
-
85083953220
-
-
Vatanen, Tommi, Raiko, Tapani, Valpola, Harri, and LeCun, Yann. Pushing stochastic gradient towards second-order methods - backpropagation learning with transformations in nonlinearities. 2013.
-
(2013)
Pushing Stochastic Gradient Towards Second-order Methods - Backpropagation Learning with Transformations in Nonlinearities
-
-
Vatanen, T.1
Raiko, T.2
Valpola, H.3
LeCun, Y.4
-
42
-
-
84965146939
-
-
arXiv: 1412.7149
-
Yang, Z., Moczulski, M., Denil, M., de Freitas, N., Smola, A., Song, L., and Wang, Z. Deep fried convnets. arXiv: 1412.7149, 2014.
-
(2014)
Deep Fried Convnets
-
-
Yang, Z.1
Moczulski, M.2
Denil, M.3
Freitas, N.4
Smola, A.5
Song, L.6
Wang, Z.7
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