<p><P><EM>Information Theory and Statistical Learning</EM> presents theoretical and practical results about information theoretic methods used in the context of statistical learning. </P><P>The book will present a comprehensive overview of the large range of different methods that have been develope
Information Theory and Statistical Learning
โ Scribed by Ray J. Solomonoff (auth.), Frank Emmert-Streib, Matthias Dehmer (eds.)
- Publisher
- Springer US
- Year
- 2009
- Tongue
- English
- Leaves
- 442
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Subjects
Theory of Computation; Artificial Intelligence (incl. Robotics); Mathematics of Computing; Communications Engineering, Networks; Control , Robotics, Mechatronics; Statistics, general
๐ SIMILAR VOLUMES
<p><P><EM>Information Theory and Statistical Learning</EM> presents theoretical and practical results about information theoretic methods used in the context of statistical learning. </P><P>The book will present a comprehensive overview of the large range of different methods that have been develope
<p><P><EM>Information Theory and Statistical Learning</EM> presents theoretical and practical results about information theoretic methods used in the context of statistical learning. </P><P>The book will present a comprehensive overview of the large range of different methods that have been develope
<span>The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussi