Probabilistic subspace mixture models, as proposed over the last few years, are interesting methods for learning image manifolds, i.e. nonlinear subspaces of spaces in which images are represented as vectors by their grey-values. Their lack of a glo
Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has
This book is aimed at senior undergraduates and graduate students in Engi- neering, Science, Mathematics, and Computing. It expects familiarity with calculus, probability theory, and linear algebra as taught in a rst- or second- year undergraduate c
