arXiv:1506.00019v4 [cs.LG] 17 OctA Critical Review of Recurrent Neural Networks for Sequence Learning Zachary C. Lipton

Source URL: arxiv.org

• 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

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

Source URL: people.idsia.ch

• 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

A cricket-inspired Neural Network For FeedForward Compensation and Multisensory Integration Paolo Russo, Barbara Webb, Richard Reeve, Paolo Arena, Luca Patan´e Abstract— A nonlinear feedforward compensator was designe

Source URL: homepages.inf.ed.ac.uk

30 Years of Adaptive Neural Networks: Perceptron, Madaline, and Backpropagation BERNARD WIDROW, FELLOW, IEEE,

Source URL: www-isl.stanford.edu

• Artificial neural networks
• Machine learning
• Applied mathematics
• Cybernetics
• ADALINE
• Artificial neuron
• Perceptron
• Madaline
• Backpropagation
• Feedforward neural network
• Activation function
• Bernard Widrow

Univerzita Karlova v Praze Matematicko-fyzik´aln´ı fakulta ´ PRACE ´ DIPLOMOVA

Source URL: s3-eu-west-1.amazonaws.com

• Artificial neural networks
• Neuroscience
• Applied mathematics
• Cybernetics
• Backpropagation
• Artificial neuron
• Feedforward neural network
• Neuron
• Activation function
• Sigmoid function
• Biological neural network
• Convolutional neural network

Where do features come from? Geoffrey Hinton Department of Computer Science, University of Toronto 6 King’s College Rd, M5S 3G4, Canada February 18, 2013

Source URL: www.cs.toronto.edu

• Artificial neural networks
• Restricted Boltzmann machine
• Boltzmann machine
• Autoencoder
• Backpropagation
• Feedforward neural network
• Generative model
• Connectionism
• Supervised learning
• Graphical model
• Machine learning
• Hidden Markov model

ROBERTO BATTITI, MAURO BRUNATO. The LION Way: Machine Learning plus Intelligent Optimization. LIONlab, University of Trento, Italy, Apr 2015 http://intelligentoptimization.org/LIONbook

Source URL: intelligent-optimization.org

• Artificial neural networks
• Neuroscience
• Applied mathematics
• Cybernetics
• Multilayer perceptron
• Perceptrons
• Biological neural network
• Brain
• Roberto Battiti
• Sigmoid function
• Feedforward neural network
• Types of artificial neural networks

Deep Belief Networks for phone recognition Abdel-rahman Mohamed, George Dahl, and Geoffrey Hinton Department of Computer Science University of Toronto {asamir,gdahl,hinton}@cs.toronto.edu

Source URL: www.cs.utoronto.ca

• Science
• Boltzmann machine
• Speech recognition
• Backpropagation
• Hidden Markov model
• Feedforward neural network
• Pattern recognition
• Markov chain
• DBN
• Neural networks
• Statistics
• Machine learning

Backwards Differentiation in AD and Neural Nets: Past Links and New Opportunities Paul J. Werbos1 Abstract Backwards calculation of derivatives – sometimes called the reverse mode, the full adjoint method, or backpropa

Source URL: www.werbos.com

• Mathematics
• Neuroscience
• Backpropagation
• Artificial neural network
• Automatic differentiation
• Multilayer perceptron
• Perceptron
• Derivative
• Feedforward neural network
• Neural networks
• Computational neuroscience
• Cybernetics