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Artificial Intelligence: Neural Networks: People: Page 5




People

Links

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Saul, Lawrence K.

http://www.cis.upenn.edu/~lsaul/

Machine learning, pattern recognition, neural networks, voice processing, auditory computation.

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LeCun, Yann

http://yann.lecun.com/

Handwritten recognition, convolutional networks, image compression. Noted for LeNet.

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Kearns, Michael

http://www.cis.upenn.edu/~mkearns/

Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems.

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Storkey, Amos

http://www.anc.ed.ac.uk/~amos/

Belief networks, dynamic trees, image models, image processing, probabilistic methods in astronomy, scientific data mining, Gaussian processes and Hopfield neural networks.

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Roweis, Sam T.

http://www.cs.toronto.edu/~roweis/

Speech processing, auditory scene analysis, machine learning.

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Coolen, Ton

http://www.mth.kcl.ac.uk/~tcoolen/

Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks.

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Bach, Francis

http://www.cs.berkeley.edu/~fbach/

Machine learning, kernel methods, kernel independent component analysis and graphical models

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Winther, Ole

http://eivind.imm.dtu.dk/staff/winther/

Variational algorithms for Gaussian processes, neural networks and support vector machines. Also work on belief propagation and protein structure prediction.

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Herbrich, Ralph

http://www.research.microsoft.com/users/rherb/

Statistical learning theory, support vector machines and kernel methods.

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Roberts, Stephen

http://www.robots.ox.ac.uk/~sjrob/

Machine learning and medical data analysis, independent component analysis and information theory.

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Bishop, Chris

http://research.microsoft.com/~cmbishop/

Graphical models, variational methods, pattern recognition.

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Cottrell, Garrison W.

http://charlotte.ucsd.edu/~gary/

An artrificial intelligence researcher who is an expert on neural networks.

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Frey, Brendan J.

http://www.psi.utoronto.ca/~frey/

Iterative decoding, unsupervised learning, graphical models.

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Hinton, Geoffrey E.

http://www.cs.toronto.edu/~hinton/

Unsupervised learning with rich sensory input. Most noted for being a co-inventor of back-propagation.

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MacKay, David

http://www.inference.phy.cam.ac.uk/mackay/

Bayesian theory and inference, error-correcting codes, machine learning.

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Smola, Alex J.

http://mlg.anu.edu.au/~smola/

Kernel methods for prediction and data analysis.

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Category for: Artificial Intelligence: Neural Networks: People: Page 5