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Regularized training of an autoencoder typically results in hidden unit biases that take on large negative values.
Independent component analysis , volume 46
Hyvärinen, Aapo, Karhunen, Juha, and Oja, Erkki · 2004
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Unsupervised learning of image transformations
Memisevic, Roland and Hinton, Geoffrey · 2007
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Bilinear models of natural images
Olshausen, Bruno, Cadieu, Charles, Culpepper, Jack, and Warland, David · 2007
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Unsupervised learning of invariant feature hierarchies with applications to object recognition
Ranzato, M, Huang, Fu Jie, Boureau, Y-L, and LeCun, Yann · 2007
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An Introduction to Frames
Kovacevic, J. and Chebira, A · 2008
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Sparse deep belief net model for visual area v2
Lee, Honglak, Ekanadham, Chaitanya, and Ng, Andrew · 2008
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Sparse coding via thresholding and local competition in neural circuits
Rozell, Christopher J, Johnson, Don H, Baraniuk, Richard G, and Olshausen, Bruno A · 2008
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Extracting and composing robust features with denoising autoencoders
Vincent, Pascal, Larochelle, Hugo, Bengio, Yoshua, and Manzagol, Pierre-Antoine · 2008
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Learning multiple layers of features from tiny images
Krizhevsky, Alex and Hinton, Geoffrey · 2009
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Actions in context
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A Practical Guide to Training Restricted Boltzmann Machines
Hinton, Geoffrey · 2010
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Fast inference in sparse coding algorithms with applications to object recognition
Kavukcuoglu, Koray, Ranzato, Marc’Aurelio, and LeCun, Yann · 2010
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Learning to represent spatial transformations with factored higher-order boltzmann machines
Memisevic, Roland and Hinton, Geoffrey E · 2010
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Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images
Ranzato, Marc’Aurelio, Krizhevsky, Alex, and Hinton, Geoffrey E · 2010
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Convolutional learning of spatio-temporal features
Taylor, Graham W., Fergus, Rob, LeCun, Yann, and Bregler, Christoph · 2010
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An analysis of single-layer networks in unsupervised feature learning
Coates, Adam, Lee, Honglak, and Ng, A. Y · 2011
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Improving neural networks by preventing co-adaptation of feature detectors
Hinton, Geoffrey E., Srivastava, Nitish, Krizhevsky, Alex, Sutskever, Ilya, and Salakhutdinov, Ruslan · 2012
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Adaptive dropout for training deep neural networks
Ba, Jimmy and Frey, Brendan · 2013
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Signal recovery from thresholded frame measurements
Boche, Holger, Guillemard, Mijail, Kutyniok, Gitta, and Philipp, Friedrich · 2013
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Saturating auto-encoders
Goroshin, Rotislav and LeCun, Yann · 2013
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On autoencoder scoring
Kamyshanska, Hanna and Memisevic, Roland · 2013
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Fastfood - approximating kernel expansions in loglinear time
Le, Quoc, Sarlos, Tamas, and Smola, Alex · 2013
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Courville, Aaron C, Bergstra, James, and Bengio, Yoshua · 2011
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Le, Q.V., Zou, W.Y., Yeung, S.Y., and Ng, A.Y · 2011
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Gradient-based learning of higher-order image features
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Contractive Auto-Encoders: Explicit Invariance During Feature Extraction
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Makhzani, Alireza and Frey, Brendan · 2013
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On the representational efficiency of restricted boltzmann machines
Martens, James, Chattopadhyay, Arkadev, Pitassi, Toniann, and Zemel, Richard · 2013
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The role of spatio-temporal synchrony in the encoding of motion
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On the number of inference regions of deep feed forward networks with piece-wise linear activations
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