Statistical learning theory vapnik ebook

Advertisement Hide. This service is more advanced with JavaScript available. The Nature of Statistical Learning Theory. Authors view affiliations Vladimir N. Front Matter Pages i-xv. Pages Setting of the Learning Problem. Consistency of Learning Processes.

Bounds on the Rate of Convergence of Learning Processes. Controlling the Generalization Ability of Learning Processes. Constructing Learning Algorithms. Setting of the Learning Problem.

Consistency of Learning Processes. Bounds on the Rate of Convergence of Learning Processes. Controlling the Generalization Ability of Learning Processes.

Methods of Pattern Recognition. Methods of Function Estimation. Direct Methods in Statistical Learning Theory. Back Matter Pages About this book Introduction The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization.

The second edition of the book contains three new chapters devoted to further development of the learning theory and SVM techniques.

Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists. Vladimir N. He is one of the founders of. Conditional probability Statistical Learning Statistical Theory cognition control learning pattern recognition statistics.

Authors and affiliations Vladimir N.