Most tasks require a person or an automated system to reason--to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning...

Computational experiments on algorithms can supplement theoretical analysis by showing what algorithms, implementations, and speed-up methods work best for specific machines or problems. This book guides the reader through the nuts and bolts of the major experimental questions: What should I measure? What inputs should I test? How do I...

Vision plays a fundamental role for living beings by allowing them to interact with the environment in an effective and efficient way. The Machine Vision goal is to endow computing devices, and more generally artificial systems, with visual capabilities in order to cope with not a priori predetermined situations. To this end, we have to take...

This text began as notes for a course in statistical computing for second year actuarial and statistical students at the University of Western Ontario. Both authors are interested in statistical computing, both as support for our other research and for its own sake. However, we have found that our students were not learning the right sort of...

Dr Donald Bailey starts with introductory material considering the problem of embedded image processing, and how some of the issues may be solved using parallel hardware solutions. Field programmable gate arrays (FPGAs) are introduced as a technology that provides flexible, fine-grained hardware that can readily exploit parallelism within...