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A key challenge in designing convolutional network models is sizing them appropriately.
Long short-term memory
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Sparse coding with an overcomplete basis set: A strategy employed by V1?
B. A. Olshausen and D. J. Field · 1997
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Gradient-based learning applied to document recognition
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner · 1998
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Training recurrent networks by evolino
J. Schmidhuber, D. Wierstra, M. Gagliolo, and F. Gomez · 2007
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Sparse coding via thresholding and local competition in neural circuits
C. J. Rozell, D. H. Johnson, R. G. Baraniuk, and B. A. Olshausen · 2008
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A fast iterative shrinkage-thresholding algorithm for linear inverse problems
A. Beck and M. Teboulle · 2009
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A novel connectionist system for improved unconstrained handwriting recognition
A. Graves, M. Liwicki, S. Fernandez, R. Bertolami, H. Bunke, and J. Schmidhuber · 2009
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Learning multiple layers of features from tiny images
A. Krizhevsky · 2009
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Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
H. Lee, R. Grosse, R. Ranganath, and A. Ng · 2009
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Learning fast approximations of sparse coding
K. Gregor and Y. LeCun · 2010
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Rectified linear units improve restricted boltzmann machines
V. Nair and G. E. Hinton · 2010
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Temporal kernel recurrent neural networks
I. Sutskever and G. Hinton · 2010
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Flexible, high performance convolutional neural networks for image classification
D. C. Cireşan, U. Meier, J. Masci, L. M. Gambardella, and J. Schmidhuber · 2011
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The importance of encoding versus training with sparse coding and vector quantization
A. Coates and A. Y. Ng · 2011
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Deep sparse rectifier networks
X. Glorot, A. Bordes, and Y. Bengio · 2011
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Reading digits in natural images with unsupervised feature learning
Y. Netzer, T. Wang, A. Coates, A. Bissacco, B. Wu, and A. Y. Ng · 2011
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Practical bayesian optimzation of machine learning algorithms
J. Snoek, H. Larochelle, and R. Adams · 2012
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Convolutional-Recursive Deep Learning for 3D Object Classification
R. Socher, B. Huval, B. Bhat, C. D. Manning, and A. Y. Ng · 2012
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Maxout networks
I. Goodfellow, D. Warde-Farley, M. Mirza, A. Courville, and Y. Bengio · 2013
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Multi-prediction deep boltzmann machines
I. J. Goodfellow, M. Mirza, A. Courville, and Y. Bengio · 2013
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Speech recognition with deep recurrent neural networks
A. Graves, A. Mohamed, and G. Hinton · 2013
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Discriminative recurrent sparse auto-encoders
J. Rolfe and Y. LeCun · 2013
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Parsing Natural Scenes and Natural Language with Recursive Neural Networks
R. Socher, C. C. Lin, A. Y. Ng, and C. D. Manning · 2011
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Improving neural networks by preventing co-adaptation of feature detectors
G.E. Hinton, N. Srivastave, A. Krizhevsky, I. Sutskever, and R. R. Salakhutdinov · 2012
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G.E. Hinton · 2012
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Convolutional neural networks applied to house numbers digit classification
P. Sermanet, S. Chintala, and Y. LeCun · 2012
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Regularization of neural networks using dropconnect
L. Wan, M. Zeiler, Z. Sixin, Y. LeCun, and R. Fergus · 2013
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Stochastic pooling
M. Zeiler and R. Fergus · 2013
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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2013
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Overfeat: Integrated recognition, localization and detection using convolutional networks
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun · 2014
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