This book deals with an area that is central to modern statistical science and which has also attracted the interest of outstanding researchers beyond the statistical mainstream, from computer science, and neural computing. The book gives a vital and timely overview of current work at this interface, described by contributors representing the complete spectrum of backgrounds.
Michael Titterington, Professor of Statistics, University of Glasgow
Learning in Graphical Models is the product of a mutually exciting interaction between ideas, insights, and techniques drawn from the fields of statistics, computer science, and physics. With its authoritative tutorial papers and specialist articles by leading researchers, this collection provides an indispensable guide to a rapidly expanding subject.
A.P. Dawid, Department of Statistical Science, University of College London
The state of the art presented by the experts in the field.
Ross D. Shachter, Department of Engineering-Economic Systems and Operations Research, Stanford University
