Adelson, Edward T.
Visual perception, machine vision, image processing. |
Amari, Shun-ichi
Neural network learning, information geometry. |
Appl, Martin
Reinforcement learning, soft-computing, optimization. |
Attias, Hagai
Graphical models, variational Bayes, independent factor analysis. |
Bach, Francis
Machine learning, kernel methods, kernel independent component analysis and graphical models |
Ballard, Dana H.
Visual perception with neural networks. |
Bartlett, Marian Stewart
Image analysis with unsupervised learning, face recognition, facial expression analysis. |
Beal, Matthew J.
Bayesian inference, variational methods, graphical models. |
Becker, Sue
Neural network models of learning and memory, computational neuroscience, unsupervised learning in perceptual systems. |
Beveridge, Ross
Computer vision, model-based object recognition, face recognition. |
Bishop, Chris
Graphical models, variational methods, pattern recognition. |
Boutilier, Craig
Decision making and planning under uncertainty, reinforcement learning, game theory and economic models. |
Brody, Carlos D.
Somatosensory working memory, computation with action potentials, design of complex stimuli for sensory neurophysiology. |
Brown, Andrew
Machine learning of dynamic data, graphical models and Bayesian networks, neural networks. |
Calvin, William H.
Theoretical neurophysiologist and author of The Cerebral Code, How Brains Think. |
Caruana, Rich
Multitask learning. |
Chu, Selina
Artificial intelligence, machine learning, data mining. |
Coolen, Ton
Physics of disordered systems. Working on dynamic replica theory for recurrent neural networks. |
Cottrell, Garrison W.
An artrificial intelligence researcher who is an expert on neural networks. |
Dayan , Peter
Representation and learning in neural processing systems, unsupervised learning, reinforcement learning. |
de Freitas, Nando
Bayesian inference, Markov chain Monte Carlo simulation, machine learning. |
de Sa, Virginia
Supervised and unsupervised learning, cross-modal learning. |
Dietterich, Thomas G.
Reinforcement learning, machine learning, supervised learning. |
Dovzhenko, Alexander Yu.
Neural networks for computer clusters, oscillations in neural networks |
Freeman, William T.
Bayesian perception, computer vision, image processing. |
Frey, Brendan J.
Iterative decoding, unsupervised learning, graphical models. |
Ghahramani, Zoubin
Sensorimotor control, unsupervised learning, probabilistic machine learning. |
Ghosh, Joydeep
Adaptive multi-learner systems, intelligent data analysis, data and web mining. |
Herbrich, Ralph
Statistical learning theory, support vector machines and kernel methods. |
Heskes, Tom
Learning and generalization in neural networks. |
Hinton, Geoffrey E.
Unsupervised learning with rich sensory input. Most noted for being a co-inventor of back-propagation. |
Honavar, Vasant
Constructive learning, computational learning theory, spatial learning, cognitive modelling, incremental learning. |
Hopfield, John J.
Neural networks, collective behaviour of systems of simple processors. Most noted for Hopfield networks. |
Jaakkola, Tommi S.
Graphical models, variational methods, kernel methods. |
Jensen, Finn Verner
Graphical models, belief propagation. |
Joachims, Thorsten
Support vector machines, machine learning and natural language, statistical learning theory, text classification. |
Jordan, Michael I.
Graphical models, variational methods, machine learning, reasoning under uncertainty. |
Kakade, Sham
Reinforcement learning and conditioning, mathematical models of neural processing. |
Kali, Szabolcs
Learning and memory in the brain, hippocampus. |
Kappen, Bert
Boltzmann machines, computational neurobiology, online learning. |
Kawato, Mitsuo
Computational neuroscience, neural network modelling. |
Kearns, Michael
Reinforcement learning, probabilistic reasoning, machine learning, spoken dialogue systems. |
Keysers, Daniel
Pattern recognition and statistical modelling for object recognition. |
Koller, Daphne
Probabilistic models for complex uncertain domains. |
Lafferty, John D.
Statistical machine learning, text and natural language processing, information retrieval, information theory. |
Lawrence, Neil
Graphical models, variational methods. |
Lawrence, Steve
Information dissemination and retrieval, machine learning and neural networks. |
LeCun, Yann
Handwritten recognition, convolutional networks, image compression. Noted for LeNet. |
Leen, Todd
Online learning, machine learning, learning dynamics. |
Leow, Wee Kheng
Computer vision, computational olfaction. |
Lerner, Uri N.
Hybrid and Bayesian networks. |
Li, Zhaoping
Non-linear neural dynamics, visual segmentation, sensory processing. |
Maass, Wolfgang
Theory of computation, computation in spiking neurons. |
MacKay, David
Bayesian theory and inference, error-correcting codes, machine learning. |
McCallum, Andrew
Machine learning, text and information retrieval and extraction, reinforcement learning. |
Meila, Marina
Graphical models, learning in high dimensions, tree networks. |
Minka, Thomas P.
Machine learning, computer vision, Bayesian methods. |
Morris, Quaid
Machine learning for medical diagnosis and biological data analysis. |
Murphy, Kevin P.
Graphical models, machine learning, reinforcement learning. |
Murray, Alan
Neural networks and VLSI hardware. |
Neal, Radford
Bayesian inference, Markov chain Monte Carlo methods, evaluation of learning methods, data compression. |
Ng, Andrew
Reinforcement learning, machine learning. |
Oja, Erkki
Unsupervised learning, PCA, ICA, SOM, statistical pattern recognition, image and signal analysis. |
Olshausen, Bruno
Visual coding, statistics of images, independent components analysis. |
Opper, Manfred
Statistical physics, information theory and applied probability and applications to machien learning and complex systems. |
Paccanaro, Alberto
Learning distributed representation of concepts from relational data. |
Pathegama, Mahinda
Intelligent information systems, physiological sciences systems. |
Phillips, Jonathon
Face recognition. |
Rao, Rajesh P. N.
Models of human and computer vision. |
Rasmussen, Carl Edward
Gaussian processes, non-linear Bayesian inference, evaluation and comparison of network models. |
Revow, Michael
Hand-written character recognition. |
Roberts, Stephen
Machine learning and medical data analysis, independent component analysis and information theory. |
Rovetta, Stefano
Research on Machine Learning/Neural Networks/Clustering. Applications to DNA microarray data analysis/industrial automation/information retrieval. Teaching activities. |
Roweis, Sam T.
Speech processing, auditory scene analysis, machine learning. |
Saad, David
Neural computing, error-correcting codes and cryptography using statistical and statistical mechanics techniques. |
Sahani, Maneesh
Statistical analysis of neural data, experimental design in neuroscience. |
Sallans, Brian
Decision making under uncertainty, reinforcement learning, unsupervised learning. |
Saul, Lawrence K.
Machine learning, pattern recognition, neural networks, voice processing, auditory computation. |
Saund, Eric
Intermediate level structure in vision. |
Schetinin, Vitaly
Biomedical data mining, diagnostic rule extraction and quality control in industry using a variety of techniques. |
Sejnowski, Terry
Sensory representation in visual cortex, memory representation and adaptive organization of visuo-motor transformations. |
Seung, Sebastian
Short-term memory, learning and memory in the brain, computational learning theory. |
Shuurmans, Dale
Computational learning, complex probability modelling. |
Simard, Patrice
Machine learning and generalization. |
Smola, Alex J.
Kernel methods for prediction and data analysis. |
Storkey, Amos
Belief networks, Dynamic Trees, Probabilistic Methods in Astronomy, Gaussian processes and Hopfield Neural Networks. |
Sutton, Richard S.
Reinforcement learning. |
Teh, Yee Whye
Learning and inference in complex probabilistic models. |
Tishby, Naftali
Machine learning; applications to human-computer interaction, vision,neurophysiology, biology and cognitive science. |
Tong, Simon
Machine learning, active learning, graphical models, support vector machines. |
Wainwright, Martin
Statistical signal and image processing, natural image modelling, graphical models. |
Wallis, Guy
Object recognition, cognitive neuroscience, interaction between vision and motor movements. |
Weiss, Yair
Vision, Bayesian methods, neural computation. |
Welling, Max
Unsupervised learning, probabilistic density estimation, machine vision. |
Wiegerinck, Wim
Inference in graphical models, mean field and variational approaches. |
Williams, Christopher K. I.
Gaussian processes, image interpretation, graphical models, pattern recognition. |
Winther, Ole
Variational algorithms for Gaussian processes, neural networks and support vector machines. Also work on belief propagation and protein structure prediction. |
Wiskott, Laurenz
Face recognition, Invariances in learning and vision. |
Wu, Yingnian
Stochastic generative models for complex visual phenomena. |
Wunsch II, Donald C.
Reinforcement Learning, Adaptive Critic Designs, Control, Optimization, Graph Theory, Bioinformatics, Intrusion Detection. |
Yedidia, Jonathan S.
Statistical methods for inference and learning. |
Zemel, Richard
Unsupervised learning, machine learning, computational models of neural processing. |
Zhu, Song Chun
Vision and graphics, statistical modelling and computing, neural computation. |
