Gaussian Processes for Machine Learning (2006)
Rasmussen, C.E., Williams, C.K.I.
Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past...
On the eigenspectrum of the gram matrix and the generalization error of kernel-PCA (2005)
Shawe-Taylor, J., Williams, C.K.I., Cristianini, N., Kandola, J.
In this paper, the relationships between the eigenvalues of the m/spl times/m Gram matrix K for a kernel /spl kappa/(/spl middot/,/spl middot/) corresponding to a sample x/sub 1/,...,x/sub m/ drawn...
Greedy Learning of Multiple Objects in Images using Robust Statistics and Factorial Learning (2004)
We consider data that are images containing views of multiple objects. Our task is to learn about each of the objects present in the images. This task can be approached as a factorial learning...
Cleaning sky survey databases using Hough Transform and Renewal String approaches (2003)
Storkey, A. J., Hambly, N. C., Williams, C. K. I., Mann, R. G.
Large astronomical databases obtained from sky surveys such as the SuperCOSMOS Sky Survey (SSS) invariably suffer from spurious records coming from artefactual effects of the telescope, satellites...