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Neural backpropagation
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151	MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Discriminatively Trained Recurrent Neural Networks for Single-Channel Speech Separation Add to Reading List Source URL: www.merl.com Language: English - Date: 2014-12-26 16:03:14 Computational neuroscience Science Long short term memory Speech recognition Non-negative matrix factorization Recurrent neural network International Conference on Acoustics Speech and Signal Processing Backpropagation through time Discrete Fourier transform Neural networks Algebra Mathematics
152	A COURSE IN NEURAL NETWORKS FOR SYSTEM IDENTIFICATION AND CONTROL ___________________________________________________________________________ Goal: Add to Reading List Source URL: www.iau.dtu.dk Language: English - Date: 2000-02-15 12:20:17 Cybernetics Applied mathematics Econometrics Network architecture Networks Control theory Backpropagation Mathematical optimization Cellular neural network Neural networks Computational neuroscience Science
153	Artificial Neural Networks Examination, March 2002 Instructions There are SIXTY questions (worth up to 60 marks). The exam mark (maximum 60) will be added to the mark obtained in the laborations (maximum 5). The total pa Add to Reading List Source URL: aass.oru.se Language: English - Date: 2004-06-07 09:38:12 Statistics Perceptron Artificial neural network Multilayer perceptron Activation function Backpropagation ADALINE Supervised learning Competitive learning Neural networks Machine learning Cybernetics
154	Artificial Neural Networks Examination, June/August 2003 Instructions There are SIXTY questions (worth up to 60 marks). The exam mark (maximum 60) will be added to the mark obtained in the laborations (maximum 5). The to Add to Reading List Source URL: aass.oru.se Language: English - Date: 2004-06-07 09:38:12 Statistics Perceptron Artificial neural network Multilayer perceptron Generalization error Backpropagation Supervised learning Statistical classification Pattern recognition Neural networks Machine learning Cybernetics
155	Artificial Neural Networks Examination, June 2005 Instructions There are SIXTY questions. (The pass mark is 30 out of 60). For each question, please select a maximum of ONE of the given answers (either A, B, C, D or E). Add to Reading List Source URL: aass.oru.se Language: English - Date: 2005-06-05 12:55:59 Artificial intelligence Perceptron Artificial neural network Feedforward neural network Multilayer perceptron Backpropagation Generalization error Statistical classification ADALINE Neural networks Cybernetics Science
156	Cognition–394 Contents lists available at ScienceDirect Cognition journal homepage: www.elsevier.com/locate/COGNIT Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English - Date: 2009-04-07 02:52:24 Ethology Cognitive science Computational neuroscience Long short term memory Motor control Recurrent neural network Prefrontal Cortex Basal Ganglia Working Memory Backpropagation Working memory Neural networks Mind Neuroscience
157	C2FS: An Algorithm for Feature Selection in Cascade Neural Networks Lars Backstrom Rich Caruana Computer Science Add to Reading List Source URL: www.cs.cornell.edu Language: English - Date: 2006-09-13 16:02:40 Cybernetics Early stopping Backpropagation Feature selection Artificial neural network Algorithm Artificial neuron Feature Overfitting Neural networks Statistics Machine learning
158	Practical Issues in Temporal Diﬀerence Learning∗ Gerald Tesauro IBM Thomas J. Watson Research Center PO Box 704, Yorktown Heights, NYUSA Abstract. This paper examines whether temporal diﬀerence methods for t Add to Reading List Source URL: aass.oru.se Language: English - Date: 2005-06-14 12:26:47 Learning Neural networks Reinforcement learning Supervised learning Temporal difference learning Backgammon E-learning Algorithm Backpropagation Machine learning Computational neuroscience Games
159	Artificial Neural Networks Examination, March 2003 Instructions There are SIXTY questions (worth up to 60 marks). The exam mark (maximum 60) will be added to the mark obtained in the laborations (maximum 5). The total pa Add to Reading List Source URL: aass.oru.se Language: English - Date: 2004-06-07 09:38:12 Neuroscience Perceptron Artificial neural network Multilayer perceptron Backpropagation Pattern recognition Statistical classification Winner-take-all Activation function Neural networks Cybernetics Science
160	Artificial Neural Networks Examination, March 2004 Instructions There are SIXTY questions (worth up to 60 marks). The exam mark (maximum 60) will be added to the mark obtained in the laborations (maximum 5). The total pa Add to Reading List Source URL: aass.oru.se Language: English - Date: 2004-06-07 09:38:12 Artificial intelligence Feedforward neural network Perceptron Artificial neuron Artificial neural network Multilayer perceptron Backpropagation Generalization error ADALINE Neural networks Cybernetics Science

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