
This book presents revised lectures of two subsequent summer schools held in 2003 in Canberra, Australia, and in TA1/4bingen, Germany. The tutorial lectures included are devoted to statistical learning theory, unsupervised learning, Bayesian inference, and applications in pattern recognition; they provide in-depth overviews of exciting new developments and contain a large number of references.
Graduate students, lecturers, researchers and professionals alike will find this book a useful resource in learning and teaching machine learning.
| w a butterfield p a beddome y bai aronson j k frederick kiley | w a bartlett robert mcnab v a glover bob ohnstad w a craigie |