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Neural backpropagation
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51	Workshop track - ICLRF EED -F ORWARD N ETWORKS WITH ATTENTION C AN S OLVE S OME L ONG -T ERM M EMORY P ROBLEMS Daniel P. W. Ellis LabROSA, Columbia University Add to Reading List Source URL: colinraffel.com Language: English - Date: 2016-03-27 22:53:26 Artificial neural networks Computational neuroscience Artificial intelligence Computational statistics Deep learning Recurrent neural network Speech recognition Sepp Hochreiter Long short-term memory Yoshua Bengio Backpropagation through time Memory
52	IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 8, NO. 6, NOVEMBERNonlinear Backpropagation: Doing Backpropagation Without Derivatives of the Activation Function Add to Reading List Source URL: people.binf.ku.dk Language: English - Date: 2005-11-10 10:33:06
53	Evolving Large-Scale Neural Networks for Vision-Based Reinforcement Learning Jan Koutník Giuseppe Cuccu Add to Reading List Source URL: people.idsia.ch Language: English - Date: 2013-08-16 10:17:44 Artificial neural networks Cybernetics Applied mathematics Machine learning Recurrent neural network Backpropagation Jrgen Schmidhuber Deep learning Types of artificial neural networks
54	INTRODUCTION TO MACHINE LEARNING AN EARLY DRAFT OF A PROPOSED TEXTBOOK Add to Reading List Source URL: robotics.stanford.edu Language: English - Date: 2010-06-21 13:24:18 Learning Machine learning Education Cognition Artificial neural networks Educational psychology Computational neuroscience Computational statistics Supervised learning Computational learning theory Backpropagation Statistical learning theory
55	Backpropagation without Human Supervision for Visual Control in Quake II Matt Parker and Bobby D. Bryant Abstract— Backpropagation and neuroevolution are used in a Lamarckian evolution process to train a neural network Add to Reading List Source URL: www.cse.unr.edu Language: English - Date: 2012-06-18 19:31:11
56	Lamarckian Neuroevolution for Visual Control in the Quake II Environment Matt Parker and Bobby D. Bryant Abstract— A combination of backpropagation and neuroevolution is used to train a neural network visual controller Add to Reading List Source URL: www.cse.unr.edu Language: English - Date: 2012-06-18 19:31:11
57	Sequence-to-Sequence Neural Net Models for Grapheme-to-Phoneme Conversion Kaisheng Yao, Geoffrey Zweig Microsoft Research {kaisheny, gzweig}@microsoft.com Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2015-05-31 01:20:23 Artificial neural networks Machine learning Applied mathematics Cybernetics Long short-term memory Recurrent neural network Speech recognition Bidirectional recurrent neural networks Artificial intelligence Language model NETtalk Backpropagation through time
58	30 Years of Adaptive Neural Networks: Perceptron, Madaline, and Backpropagation BERNARD WIDROW, FELLOW, IEEE, Add to Reading List Source URL: www-isl.stanford.edu Language: English - Date: 2008-03-07 20:14:11 Artificial neural networks Machine learning Applied mathematics Cybernetics ADALINE Artificial neuron Perceptron Madaline Backpropagation Feedforward neural network Activation function Bernard Widrow
59	1109 IEEE TRANSACTIONS ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL 36, NO 7, JULY 1988 Layered Neural Nets for Pattern Recognition BERNARD WIDROW, FELLOW,IEEE, RODNEY G. WINTER, Add to Reading List Source URL: www-isl.stanford.edu Language: English - Date: 2008-02-08 00:24:44 Artificial neural networks Artificial neuron ADALINE Backpropagation Adaptive filter Types of artificial neural networks Perceptron
60	Improving the Learning Speed of 2-Layer Neural Networks by Choosing Initial Values of the Adaptive Weights Derrick Nguyen and Bernard Widrow Information Systems Laboratory Stanford University Stanford, CA 94305 Add to Reading List Source URL: www-isl.stanford.edu Language: English - Date: 2008-03-07 21:10:07 Artificial neural networks Applied mathematics Cybernetics Statistics Backpropagation Artificial neuron Perceptron Sigmoid function Activation function Deep learning

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