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Boltzmann machine
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#	Item
81	On the Representational Efficiency of Restricted Boltzmann Machines James Martens∗ ∗ Arkadev Chattopadhyay+ Add to Reading List Source URL: papers.nips.cc Language: English - Date: 2014-11-25 16:06:54 Statistics Boltzmann machine Perceptron Backpropagation Activation function Logistic function Neural networks Cybernetics Mathematics
82	Exploring Compositional High Order Pattern Potentials for Structured Output Learning Yujia Li, Daniel Tarlow, Richard Zemel University of Toronto Toronto, ON, Canada, M5S 3G4 {yujiali, dtarlow, zemel}@cs.toronto.edu Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2013-04-19 18:32:04 Graphical models Statistical models Theoretical computer science Bayesian statistics Conditional random field Boltzmann machine Expectation–maximization algorithm Mixture model Pattern recognition Statistics Machine learning Probability and statistics
83	A fast learning algorithm for deep belief nets ∗ Geoffrey E. Hinton and Simon Osindero Yee-Whye Teh Department of Computer Science University of Toronto Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2008-10-31 15:01:14 Boltzmann machine Backpropagation Generative model Artificial neuron Independent component analysis Diffusion networks Gibbs sampling Pattern recognition Expectation–maximization algorithm Neural networks Statistics Machine learning
84	Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines Kihyuk Sohn Guanyu Zhou Chansoo Lee Honglak Lee Add to Reading List Source URL: jmlr.org Language: English - Date: 2013-08-14 01:36:44 Boltzmann machine Supervised learning Feature selection Pattern recognition Generative model Neural network Unsupervised learning Support vector machine Linear classifier Statistics Machine learning Artificial intelligence
85	IMPROVING DEEP NEURAL NETWORK ACOUSTIC MODELS USING GENERALIZED MAXOUT NETWORKS Xiaohui Zhang, Jan Trmal, Daniel Povey, Sanjeev Khudanpur Center for Language and Speech Processing & Human Language Technology Center of Ex Add to Reading List Source URL: www.danielpovey.com Language: English - Date: 2014-03-06 00:47:58 Science Speech recognition Recurrent neural network Backpropagation Boltzmann machine Artificial neural network Neural networks Machine learning Cybernetics
86	IEEE-28MSP01-Feature-TEMPLATE Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2012-09-17 18:08:36 Computational neuroscience Computational statistics Computational linguistics Hidden Markov model Boltzmann machine Speech recognition Artificial neural network Backpropagation Expectation–maximization algorithm Statistics Neural networks Machine learning
87	Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model David P. Reichert, Peggy Series and Amos J. Storkey School of Informatics, University of Edinburgh 10 Crichton Street, Edin Add to Reading List Source URL: homepages.inf.ed.ac.uk Language: English Cerebrum Medical signs Psychedelics dissociatives and deliriants Psychosis Philosophy of mind Hallucination Auditory hallucination Visual cortex Cerebral cortex Anatomy Mind Cognitive science
88	1 Deep Neural Networks for Acoustic Modeling in Speech Recognition Geoffrey Hinton, Li Deng, Dong Yu, George Dahl, Abdel-rahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Tara Sainath, an Add to Reading List Source URL: static.googleusercontent.com Language: English - Date: 2012-10-26 02:52:04 Hidden Markov model Artificial neural network Boltzmann machine Generative model Feedforward neural network Speech recognition Backpropagation Expectation–maximization algorithm Latent variable Statistics Neural networks Machine learning
89	Comparing Probabilistic Models for Melodic Sequences Athina Spiliopoulou and Amos Storkey School of Informatics, University of Edinburgh, United Kingdom {a.spiliopoulou,a.storkey}@ed.ac.uk Abstract. Modelling the real w Add to Reading List Source URL: homepages.inf.ed.ac.uk Language: English - Date: 2012-04-26 12:53:52 Hidden Markov model Boltzmann machine Generative model Graphical model N-gram Markov model Gibbs sampling Latent variable Statistics Statistical models Probability
90	LEARNING HIDDEN UNIT CONTRIBUTIONS FOR UNSUPERVISED SPEAKER ADAPTATION OF NEURAL NETWORK ACOUSTIC MODELS Pawel Swietojanski and Steve Renals Centre for Speech Technology Research, University of Edinburgh, Edinburgh EH8 9 Add to Reading List Source URL: www.cstr.ed.ac.uk Language: English - Date: 2014-11-17 05:17:51 Cybernetics Science Humanâ€“computer interaction Computer accessibility Speech recognition Perceptron Speaker recognition Boltzmann machine Feedforward neural network Neural networks Automatic identification and data capture Computational neuroscience

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