MEAN-NORMALIZED STOCHASTIC GRADIENT FOR LARGE-SCALE DEEP LEARNING Simon Wiesler1 , Alexander Richard1 , Ralf Schl¨uter1 , Hermann Ney1,2 1 Human Language Technology and Pattern Recognition, Computer Science Department,

Source URL: www-i6.informatik.rwth-aachen.de

• Artificial intelligence
• Perceptron
• Stochastic gradient descent
• Early stopping
• Backpropagation
• Overfitting
• Speech recognition
• Mathematical optimization
• Neural networks
• Statistics
• Cybernetics

Student Citizenship Environmental Stewardship We have a deep commitment to Environmental Stewardship. Reduce, Reuse and Recycle is a serious endeavor. This year we will focus on REDUCE as Recycle has been quite well mas

Source URL: www.tnsk.org

• Educational psychology
• Educational leadership
• Senior Project
• Service-learning
• E-learning
• Project-based learning
• Jisan Research Institute Educational Policy
• Education
• Pedagogy
• Alternative education

Recent Events Learning about Deep Water Diving 
 Ms Sims Retirement Party

Source URL: mtwash.cps-k12.org

NEW TYPES OF DEEP NEURAL NETWORK LEARNING FOR SPEECH RECOGNITION AND RELATED APPLICATIONS: AN OVERVIEW Li Deng1, Geoffrey Hinton2, and Brian Kingsbury3 1 Microsoft Research, Redmond, WA, USA 2

Source URL: www.cs.toronto.edu

• Science
• Machine learning
• Learning
• Artificial intelligence
• Backpropagation
• Speech recognition
• Recurrent neural network
• Boltzmann machine
• Supervised learning
• Neural networks
• Computational neuroscience
• Cybernetics

Deep Mixtures of Factor Analysers Yichuan Tang [removed] Ruslan Salakhutdinov [removed]

Source URL: www.cs.toronto.edu

• Machine learning
• Data analysis
• Multivariate statistics
• Expectation–maximization algorithm
• Mixture model
• Principal component analysis
• Maximum likelihood
• Independent component analysis
• Supervised learning
• Statistics
• Statistical models
• Estimation theory

SUBMITTED TO IEEE TRANS. ON AUDIO, SPEECH, AND LANGUAGE PROCESSING 1 Acoustic Modeling using Deep Belief Networks Abdel-rahman Mohamed, George E. Dahl, and Geoffrey Hinton

Source URL: www.cs.toronto.edu

• Science
• Artificial neural network
• Boltzmann machine
• Recurrent neural network
• Feedforward neural network
• Backpropagation
• Speech recognition
• Hidden Markov model
• Early stopping
• Neural networks
• Machine learning
• Cybernetics

ARTICLE Communicated by Yoshua Bengio An Efficient Learning Procedure for Deep Boltzmann Machines

Source URL: www.cs.toronto.edu

• Statistical theory
• Neural networks
• Statistical models
• Boltzmann machine
• Bayesian statistics
• Markov chain
• Maximum likelihood
• Generative model
• Ludwig Boltzmann
• Statistics
• Estimation theory
• Probability and statistics

UNDERSTANDING HOW DEEP BELIEF NETWORKS PERFORM ACOUSTIC MODELLING Abdel-rahman Mohamed, Geoffrey Hinton, and Gerald Penn Department of Computer Science, University of Toronto ABSTRACT Deep Belief Networks (DBNs) are a ve

Source URL: www.cs.toronto.edu

• Applied mathematics
• Speech recognition
• Mel-frequency cepstrum
• Supervised learning
• Feedforward neural network
• Backpropagation
• Discrete cosine transform
• Neural networks
• Cybernetics
• Science

Learning Hierarchical Representations for Face Verification with Convolutional Deep Belief Networks Gary B. Huang University of Massachusetts Amherst, MA

Source URL: vis-www.cs.umass.edu

• Mind
• Vision
• Semi-supervised learning
• Feature
• Recall
• Visual descriptors
• Supervised learning
• Boltzmann machine
• Statistical classification
• Machine learning
• Computer vision
• Artificial intelligence

UCL Tutorial on: Deep Belief Nets (An updated and extended version of my 2007 NIPS tutorial) Geoffrey Hinton Canadian Institute for Advanced Research

Source URL: www.cs.toronto.edu

• Cybernetics
• Perceptron
• Nonlinear dimensionality reduction
• Backpropagation
• Statistical classification
• Generative model
• Types of artificial neural networks
• Feedforward neural network
• Neural networks
• Statistics
• Machine learning