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Chris Williams

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Report Date Title
EDI-INF-RR-1228 Dec 2007 A Note on Noise-free Gaussian Process Prediction with Separable Covariance Functions and Grid Designs
EDI-INF-RR-1177 Mar 2006 Using Machine Learning to Focus Iterative Optimization
EDI-INF-RR-1089 Mar 2006 Using Machine Learning to Focus Iterative Optimization
EDI-INF-RR-1036 2001 Using the Nystroem Method to Speed Up Kernel Machines
EDI-INF-RR-1015 Mar 2006 Using Machine Learning to Focus Iterative Optimization.
EDI-INF-RR-0887 Jan 2006 Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care
EDI-INF-RR-0719 Jan 2006 On a Connection between Object Localization with a Generative Template of Features and Pose-space Prediction Methods
EDI-INF-RR-0583 2006 Gaussian Processes for Machine Learning
EDI-INF-RR-0383 2003 Dynamic Trees for Image Modelling
EDI-INF-RR-0382 2005 On the Eigenspectrum of the Gram Matrix and the Generalization Error of Kernel PCA
EDI-INF-RR-0381 2002 On a Connection between Kernel PCA and Metric Multidimensional Scaling
EDI-INF-RR-0362 2004 Cleaning Sky Survey Databases using Hough Transform and Renewal String Approaches
EDI-INF-RR-0361 2003 Image modelling with position-encoding dynamic trees
EDI-INF-RR-0318 Aug 2005 An Expectation Maximisation Algorithm for One-to-Many Record Linkage, Illustrated on the Problem of Matching Far Infra-Red Astronomical Sources to Optical Counterparts
EDI-INF-RR-0259 May 2004 Greedy Learning of Multiple Objects in Images using Robust Statistics and Factorial Learning
EDI-INF-RR-0185 Dec 2003 An isotropic Gaussian mixture can have more modes than components
EDI-INF-RR-0159 Feb 2003 On the Number of Modes of a Gaussian Mixture
EDI-INF-RR-0120 May 2002 An Analysis of Contrastive Divergence Learning in Gaussian Boltzmann Machines
EDI-INF-RR-0043 Jul 2001 Products of Gaussians and Probabilistic Minor Component Analysis

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