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Autoencoder
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81	On the Expressive Power of Deep Architectures Yoshua Bengio and Olivier Delalleau Dept. IRO, Universit´e de Montr´eal. Montr´eal (QC), H3C 3J7, Canada Abstract. Deep architectures are families of functions correspondi Add to Reading List Source URL: deeplearning.cs.cmu.edu Language: English - Date: 2013-09-23 22:24:15 Science Artificial neural network Boltzmann machine Machine learning Supervised learning Unsupervised learning Autoencoder Artificial neuron Algorithm Neural networks Cybernetics Applied mathematics
82	Greedy Layer-Wise Training of Deep Networks Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle Universit´e de Montr´eal Montr´eal, Qu´ebec {bengioy,lamblinp,popovicd,larocheh}@iro.umontreal.ca Add to Reading List Source URL: deeplearning.cs.cmu.edu Language: English - Date: 2013-10-16 13:22:11 Artificial intelligence Computational neuroscience Network architecture Recurrent neural network Feedforward neural network Unsupervised learning Autoencoder Supervised learning Boltzmann machine Neural networks Machine learning Cybernetics
83	Dynamics of learning in deep linear neural networks Andrew M. Saxe ([removed]) Department of Electrical Engineering James L. McClelland ([removed]) Add to Reading List Source URL: www.stanford.edu Language: English - Date: 2013-11-28 10:28:30 Science Backpropagation Autoencoder Feedforward neural network Synaptic weight Artificial neural network Types of artificial neural networks Neural networks Machine learning Cybernetics
84	Outline • • • • • Add to Reading List Source URL: deeplearning.cs.cmu.edu Language: English - Date: 2013-09-16 13:15:52 Science Neuroscience Artificial neuron Activation function Multilayer perceptron Autoencoder Neural networks Cybernetics Backpropagation
85	Greedy Layer-Wise Training of Deep Networks Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle NIPS 2007 Presented by Ahmed Hefny Add to Reading List Source URL: deeplearning.cs.cmu.edu Language: English - Date: 2013-10-23 13:30:29 Networks Graphical model Autoencoder Cybernetics Science Neural networks Computational neuroscience Statistics
86	Efficient Learning of Sparse Representations with an Energy-Based Model Marc’Aurelio Ranzato Christopher Poultney Sumit Chopra Yann LeCun Courant Institute of Mathematical Sciences New York University, New York, NY 100 Add to Reading List Source URL: deeplearning.cs.cmu.edu Language: English - Date: 2013-10-16 13:22:12 Overcompleteness Supervised learning Decoder Encoder Autoencoder Matrix decoder Mathematics Digital circuits Neural networks Linear algebra
87	Deep Sparse Rectifier Neural Networks Xavier Glorot Add to Reading List Source URL: eprints.pascal-network.org Language: English - Date: 2011-06-30 04:28:55 Science Artificial neural network Activation function Backpropagation Feedforward neural network Artificial neuron Autoencoder Sigmoid function Boltzmann machine Neural networks Machine learning Cybernetics
88	ImageNet Classification with Deep Convolutional Neural Networks Alex Krizhevsky Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2012-12-30 16:45:43 Science Feedforward neural network Autoencoder Backpropagation Supervised learning Neural networks Cybernetics Statistics
89	Efficient Learning of Sparse Representations with an Energy-Based Model Add to Reading List Source URL: yann.lecun.com Language: English - Date: 2007-08-24 18:19:47 Overcompleteness Supervised learning Decoder Encoder Autoencoder Matrix decoder Mathematics Digital circuits Neural networks Linear algebra
90	PDF Document Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2013-06-21 22:11:01 Markov models Computational neuroscience Science Speech recognition Computational linguistics Hidden Markov model HTK Artificial neural network Autoencoder Neural networks Machine learning Statistics

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