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Abstract. In this paper we first overview the main concepts of Statistical Learning Theory, a framework in which learning from examples can be studied in a principled way. We then briefly discuss well known as well as emerging learning techniques such as Regularization Networks and Support Vector Machines which can
1 Introduction. The main goal of statistical learning theory is to provide a framework for study- ing the problem of inference, . graphs have been written on pattern classification and statistical learning theory. A partial list includes Anthony and Bartlett .. 3.6 Summary and Perspective. At this point, we can summarize what we
An overview of statistical learning theory. Abstract: Statistical learning theory was introduced in the late 1960's. Until the 1990's it was a purely theoretical analysis of the problem of function estimation from a given collection of data.
In the middle of the 1990's new types of learning algorithms (called support vector machines) based on the developed theory were proposed. This article presents a very general overview of statistical learning theory including both theoretical and algorithmic aspects of the theory.
Statistical Learning Theory: A Tutorial. Sanjeev R. Kulkarni and Gilbert Harman?. February 20, 2011. Abstract. In this article, we provide a tutorial overview of some aspects of statistical learning theory, which also goes by other names such as statistical pattern recognition, nonparametric classification and estimation, and
7 Dec 2017 On Jan 1, 2000, Vladimir N. Vapnik published the chapter: The Nature of Statistical Learning Theory in the book: The Nature of Statistical Learning Theory.

IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 10, NO. 5, SEPTEMBER 1999. An Overview of Statistical Learning Theory. Vladimir N. Vapnik. Abstract—Statistical learning theory was introduced in the late. 1960's. Until the 1990's it was a purely theoretical analysis of the problem of function estimation from a given
19 Dec 2013 An Introduction to Statistical. Learning. Gareth James. Daniela Witten. Trevor Hastie. Robert Tibshirani. An Introduction to Statistical Learning with Applications in R Preface. Statistical learning refers to a set of tools for modeling and understanding complex datasets. . 4.1 An Overview of Classification .
27 Apr 2011 A joint endeavor from leading researchers in the fields of philosophy and electrical engineering, An Elementary Introduction to Statistical Learning Theory is a comprehensive and accessible primer on the rapidly evolving fields of statistical pattern recognition and statistical learning theory. Explaining these

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February 2018