Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for rese

An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and

This textbook presents fundamental machine learning concepts in an easy to understand manner by providing practical advice, using straightforward examples, and

This introduction to the concepts and techniques of formal learning theory is based on a number-theoretical approach to learning and uses the tools of recursive

This volume develops an effective theory approach to understanding deep neural networks of practical relevance.