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.
Xing, Eric
Statistical learning, machine learning approaches to computational biology, pattern recognition and control.
Yedidia, Jonathan S.
Statistical methods for inference and learning.
Zemel, Richard
Unsupervised learning, machine learning, computational models of neural processing.
Zhou, Zhi-Hua
Neural computing, data mining, evolutionary computing, ensemble networks.
Adelson, Edward T.
Visual perception, machine vision, image processing.
Agakov, Felix
Probabilistic graphical modeling, statistical learning theory, pattern recognition, prediction, and causality.
Allan, Moray
Computer vision, probabilistic models for image sequences, invariant features.
Amari, Shun-ichi
Neural network learning, information geometry.
Andonie, Razvan
Data structures for computational intelligence.
Andrieu, Christophe
Particle filtering and Monte Carlo Markov Chain methods.
Anthony, Martin
Computational learning theory, discrete mathematics.
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.
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