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We seek to improve deep neural networks by generalizing the pooling operations that play a central role in current architectures.
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
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Visualizing data using t-SNE
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What is the best multi-stage architecture for object recognition?
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Learning Multiple Layers of Features from Tiny Images
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A Theoretical Analysis of Feature Pooling in Visual Recognition
Y. Boureau, J. Ponce, and Y. LeCun · 2010
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Evaluation of pooling operations in convolutional architectures for object recognition
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Ask the locals: multi-way local pooling for image recognition
Y. Boureau, N. Le Roux, F. Bach, J. Ponce, and Y. LeCun · 2011
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Selecting receptive fields in deep networks
A. Coates and A. Y. Ng · 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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Beyond spatial pyramids
Y. Jia, C. Huang, and T. Darrell · 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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Maxout Networks
I. J. Goodfellow, D. Warde-Farley, M. Mirza, A. C. Courville, and Y. Bengio · 2013
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Spatial pyramid pooling in deep convolutional networks for visual recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2014
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Autoencoder Trees
O. Irsoy and E. Alpaydin · 2014
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ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2014
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Improving deep neural networks with probabilistic maxout units
J. T. Springenberg and M. Riedmiller · 2014
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Deep Networks with Internal Selective Attention through Feedback Connections
M. Stollenga, J. Masci, F. J. Gomez, and J. Schmidhuber · 2014
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Regularization of NNs using DropConnect
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Network in network
M. Lin, Q. Chen, and S. Yan · 2013
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Discriminative transfer learning with tree-based priors
N. Srivastava and R. R. Salakhutdinov · 2013
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Stochastic Pooling for Regularization of Deep Convolutional Neural Networks
M. D. Zeiler and R. Fergus · 2013
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Neural Decision Forests for Semantic Image Labelling
S. R. Bulo and P. Kontschieder · 2014
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B. Graham · 2014
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C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2014
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Learning activation functions to improve deep neural networks
F. Agostinelli, M. Hoffman, P. Sadowski, and P. Baldi · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
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Recurrent CNNs for Object Recognition
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Striving for Simplicity
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