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Deep learning
Results: 859

#	Item
841	Deep Learning – Fall 2013 Instructor: Bhiksha Raj Paper: T. D. Sanger, “Optimal Unsupervised Learning in a Single-Layer Linear Feedforward Neural Network”, Neural Networks, vol. 2, pp[removed], 1989. Add to Reading List Source URL: deeplearning.cs.cmu.edu Language: English - Date: 2013-09-11 13:17:38 Cybernetics Generalized Hebbian Algorithm Principal component analysis Hebbian theory Artificial neuron Eigenvalues and eigenvectors Feedforward neural network Matrix Supervised learning Neural networks Algebra Mathematics
842	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
843	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
844	Multi-column Deep Neural Networks for Image Classification Dan Cires¸an, Ueli Meier and J¨urgen Schmidhuber IDSIA-USI-SUPSI Galleria 2, 6928 Manno-Lugano, Switzerland {dan,ueli,juergen}@idsia.ch Add to Reading List Source URL: deeplearning.cs.cmu.edu Language: English - Date: 2013-10-24 15:07:54 Science Artificial neural network Backpropagation Recurrent neural network Multilayer perceptron Perceptron Supervised learning Handwriting recognition Neural networks Cybernetics Artificial intelligence
845	A Fast Learning Algorithm for Deep Belief Nets Hinton, Osindero, Teh Conditional Learning is Hard Add to Reading List Source URL: deeplearning.cs.cmu.edu - Date: 2013-10-23 13:28:12
846	Kernel Methods for Deep Learning Youngmin Cho and Lawrence K. Saul Department of Computer Science and Engineering University of California, San Diego 9500 Gilman Drive, Mail Code 0404 Add to Reading List Source URL: cseweb.ucsd.edu Language: English - Date: 2009-10-01 14:38:18 Statistical classification Non-parametric statistics Support vector machine Signal processing Kernel Activation function Linux kernel Trigonometric functions Supervised learning Statistics Machine learning Neural networks
847	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
848	Bain on Neural Networks[removed]: Deep Learning Seminar Presentation on “Bain on Neural Networks” (Wilkes and Wade) Lars Mahler[removed] Add to Reading List Source URL: deeplearning.cs.cmu.edu Language: English - Date: 2013-09-04 10:06:09 David Hartley Psychologists Observations on Man Neuroanatomy Associationism Neural network Nerve Sense Brain Anatomy Mind Nervous system
849	READINGS IN DEEP LEARNING 4 Sep 2013 ADMINSTRIVIA • New course numbers[removed]are assigned – Should be up on the hub shortly Add to Reading List Source URL: deeplearning.cs.cmu.edu Language: English - Date: 2013-09-04 12:05:29 Science Neuroscience Perceptron Feedforward neural network Connectionism Bernard Widrow Hebbian theory Supervised learning Computational neuroscience Neural networks Cybernetics
850	Convolutional-Recursive Deep Learning for 3D Object Classification Richard Socher, Brody Huval, Bharath Bhat, Christopher D. Manning, Andrew Y. Ng Computer Science Department, Stanford University, Stanford, CA 94305, USA Add to Reading List Source URL: deeplearning.cs.cmu.edu Language: English - Date: 2013-10-24 15:06:58 Neural networks Computational neuroscience Supervised learning Yann LeCun Unsupervised learning Statistical classification Object recognition Segmentation Support vector machine Artificial intelligence Machine learning Statistics

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