An elementary introduction to statistical learning theory / Sanjeev Kulkarni, Gilbert Harman. An elementary introduction to statistical learning theory Kulkarni, Sanjeev. Harman, Gilbert. Machine learning Statistical methods. Pattern recognition systems. Q325.5 .K85 2011 006.31 22 KUE Includes bibliographical references and indexes. "A joint endeavor from leading researchers in the fields of philosophy and electrical engineering An Introduction to Statistical Learning Theory provides a broad and accessible introduction to rapidly evolving field of statistical pattern recognition and statistical learning theory. Exploring topics that are not often covered in introductory level books on statistical learning theory, including PAC learning, VC dimension, and simplicity, the authors present upper-undergraduate and graduate levels with the basic theory behind contemporary machine learning and uniquely suggest it serves as an excellent framework for philosophical thinking about inductive inference"--Back cover. Hoboken, N.J. : Wiley, c2011. c2011. 2011 Text xi, 209 p.: eng Wiley series in probability and statistics Wiley series in probability and statistics.