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Neural backpropagation
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41	Learning Deep Convolutional Neural Networks for Places2 Scene Recognition WM Team Li Shen Add to Reading List Source URL: image-net.org Language: English - Date: 2015-12-21 12:22:54 Artificial neural networks Backpropagation
42	CS 224d: Assignment #2 Sunday 8th May, 2016 Due date: 5/5 11:59 PM PST (You are allowed to use three (3) late days maximum for this assignment) This handout consists of several homework problems, as well as instructions Add to Reading List Source URL: cs224d.stanford.edu Language: English - Date: 2016-05-14 14:03:09 Artificial neural networks Computational neuroscience Softmax function Entropy Backpropagation Cross entropy Perplexity
43	REVIEW doi:nature14539 Deep learning Yann LeCun1,2, Yoshua Bengio3 & Geoffrey Hinton4,5 Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2015-08-10 12:54:32 Artificial neural networks Deep learning Convolutional neural network Recurrent neural network Backpropagation Autoencoder Feature learning Recursive neural network Long short-term memory Perceptron Feedforward neural network Artificial intelligence
44	AUTOMATIC MAP FEATURE EXTRACTION USING ARTIFICIAL NEURAL NETWORKS Itthi Trisirisatayawong and Mark R. Shortis Department of Geomatics University of Melbourne Parkville VIC 3052 AUSTRALIA Add to Reading List Source URL: mapcontext.com Language: English - Date: 2008-08-29 22:23:47 Machine learning Artificial neural networks Computational neuroscience Computational statistics Mathematical psychology Pattern recognition Backpropagation Statistical classification Image segmentation Supervised learning Deep learning Book:Machine Learning The Complete Guide
45	PAC Learning and Artificial Neural Networks Martin Anthony and Norman Biggs Department of Mathematics, London School of Economics and Political Science (University of London), Houghton St., London WC2A 2AE, United Kingdo Add to Reading List Source URL: www.maths.lse.ac.uk Language: English - Date: 2000-04-03 14:19:07 Computational learning theory Artificial neural networks Machine learning Computational statistics Learning VC dimension Sample complexity Probably approximately correct learning Backpropagation Perceptron Vladimir Vapnik Radial basis function network
46	arXiv:1506.00019v4 [cs.LG] 17 OctA Critical Review of Recurrent Neural Networks for Sequence Learning Zachary C. Lipton Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-10-19 21:37:55 Artificial neural networks Cybernetics Applied mathematics Machine learning Recurrent neural network Deep learning Long short-term memory Feedforward neural network Convolutional neural network Backpropagation Connectionism Restricted Boltzmann machine
47	Theano Tutorial Theano is a software package which allows you to write symbolic code and compile it onto diﬀerent architectures (in particular, CPU and GPU). It was developed by machine learning researchers at the Univ Add to Reading List Source URL: colinraffel.com Language: English - Date: 2015-12-30 23:12:51 Artificial neural networks Sigmoid function Artificial neuron Parameter Function Gradient descent Backpropagation Multilayer perceptron Activation function Theano Default argument Artificial intelligence
48	Evolving memory cell structures for sequence learning Justin Bayer, Daan Wierstra, Julian Togelius and J¨ urgen Schmidhuber IDSIA, Galleria 2, 6928 Manno-Lugano, Switzerland {justin, daan, julian, juergen}@idsia.ch Add to Reading List Source URL: people.idsia.ch Language: English - Date: 2009-05-25 10:34:00 Artificial neural networks Machine learning Applied mathematics Cybernetics Long short-term memory Recurrent neural network Artificial intelligence Handwriting recognition Feedforward neural network Backpropagation through time Backpropagation Brain
49	Simple Evolutionary Optimization Can Rival Stochastic Gradient Descent in Neural Networks In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCONew York, NY: ACM Nominated for Best Paper Aw Add to Reading List Source URL: eplex.cs.ucf.edu Language: English - Date: 2016-04-28 14:32:32 Artificial neural networks Applied mathematics Artificial intelligence Machine learning Neuroevolution Evolutionary algorithm Deep learning Backpropagation Stochastic gradient descent HyperNEAT Genetic algorithm Multilayer perceptron
50	ADVANCES IN OPTIMIZING RECURRENT NETWORKS Yoshua Bengio, Nicolas Boulanger-Lewandowski and Razvan Pascanu arXiv:1212.0901v2 [cs.LG] 14 DecU. Montreal Add to Reading List Source URL: arxiv.org Language: English - Date: 2012-12-16 20:30:23 Artificial neural networks Applied mathematics Machine learning Cybernetics Recurrent neural network Deep learning Long short-term memory Stochastic gradient descent Convolutional neural network Rectifier Backpropagation Gradient descent

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