Improving neural networks by preventing co-adaptation of feature detectors

3 July 2012

Papers citing "Improving neural networks by preventing co-adaptation of feature detectors"

29 / 1,729 papers shown

Title
Improvements to deep convolutional neural networks for LVCSR Tara N. Sainath Brian Kingsbury Abdel-rahman Mohamed George E. Dahl G. Saon H. Soltau T. Beran Aleksandr Aravkin Bhuvana Ramabhadran 134 228 0 05 Sep 2013
Prediction of breast cancer recurrence using Classification Restricted Boltzmann Machine with Dropping Jakub M. Tomczak OOD 74 17 0 28 Aug 2013
Pylearn2: a machine learning research library Ian Goodfellow David Warde-Farley Pascal Lamblin Vincent Dumoulin M. Berk Mirza Razvan Pascanu James Bergstra Frédéric Bastien Yoshua Bengio MU 106 305 0 20 Aug 2013
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation Yoshua Bengio Nicholas Léonard Aaron Courville 423 3,159 0 15 Aug 2013
Sparse arrays of signatures for online character recognition Benjamin Graham 245 96 0 01 Aug 2013
Dropout Training as Adaptive Regularization Stefan Wager Sida I. Wang Percy Liang 140 600 0 04 Jul 2013
Hyperparameter Optimization and Boosting for Classifying Facial Expressions: How good can a "Null" Model be? James Bergstra David D. Cox 3DH 80 23 0 14 Jun 2013
Understanding Dropout: Training Multi-Layer Perceptrons with Auxiliary Independent Stochastic Neurons Kyunghyun Cho 129 6 0 12 Jun 2013
Horizontal and Vertical Ensemble with Deep Representation for Classification Jingjing Xie Bing Xu Chuang Zhang SSL 119 76 0 12 Jun 2013
Deep Generative Stochastic Networks Trainable by Backprop Yoshua Bengio Eric Thibodeau-Laufer Guillaume Alain J. Yosinski BDL 159 396 0 05 Jun 2013
Predicting Parameters in Deep Learning Misha Denil B. Shakibi Laurent Dinh MarcÁurelio Ranzato Nando de Freitas OOD 258 1,324 0 03 Jun 2013
RNADE: The real-valued neural autoregressive density-estimator Benigno Uria Iain Murray Hugo Larochelle 142 239 0 02 Jun 2013
An Analysis of the Connections Between Layers of Deep Neural Networks Eugenio Culurciello Jonghoon Jin Aysegül Dündar Jordan Taylor Bates 105 13 0 01 Jun 2013
Estimating or Propagating Gradients Through Stochastic Neurons Yoshua Bengio 132 111 0 14 May 2013
Deep Learning of Representations: Looking Forward Yoshua Bengio 225 683 0 02 May 2013
Maxout Networks Ian Goodfellow David Warde-Farley M. Berk Mirza Aaron Courville Yoshua Bengio OOD 301 2,181 0 18 Feb 2013
Regularization and nonlinearities for neural language models: when are they needed? Marius Pachitariu M. Sahani 113 46 0 23 Jan 2013
Piecewise Linear Multilayer Perceptrons and Dropout Ian Goodfellow 101 6 0 22 Jan 2013
Knowledge Matters: Importance of Prior Information for Optimization Çağlar Gülçehre Yoshua Bengio 133 166 0 17 Jan 2013
Discriminative Recurrent Sparse Auto-Encoders J. Rolfe Yann LeCun BDL 147 73 0 16 Jan 2013
Training Neural Networks with Stochastic Hessian-Free Optimization Ryan Kiros BDL 102 48 0 16 Jan 2013
Big Neural Networks Waste Capacity Yann N. Dauphin Yoshua Bengio 125 84 0 16 Jan 2013
Indoor Semantic Segmentation using depth information Camille Couprie C. Farabet Laurent Najman Yann LeCun SSeg MDE 177 482 0 16 Jan 2013
Joint Training Deep Boltzmann Machines for Classification Ian Goodfellow Aaron Courville Yoshua Bengio 113 23 0 16 Jan 2013
Stochastic Pooling for Regularization of Deep Convolutional Neural Networks Matthew D. Zeiler Rob Fergus 220 990 0 16 Jan 2013
Pushing Stochastic Gradient towards Second-Order Methods -- Backpropagation Learning with Transformations in Nonlinearities T. Vatanen T. Raiko Harri Valpola Yann LeCun ODL 97 34 0 15 Jan 2013
Joint Training of Deep Boltzmann Machines Ian Goodfellow Aaron Courville Yoshua Bengio FedML 134 28 0 12 Dec 2012
Temporal Autoencoding Restricted Boltzmann Machine Chris Häusler Alex K. Susemihl AI4CE 77 8 0 31 Oct 2012
Distributed Fault Detection in Sensor Networks using a Recurrent Neural Network Oliver Obst 93 33 0 23 Jun 2009