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/08/25 16:31
"... the fact that a collection of chapters can never be as homogeneous as a book conceived by a single person. We have tried to compensate for this by the selection and refereeing process of the submissions. In addition, we have written an introductory chapter describing the SV algorithm in some detail ..."
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the fact that a collection of chapters can never be as homogeneous as a book conceived by a single person. We have tried to compensate for this by the selection and refereeing process of the submissions. In addition, we have written an introductory chapter describing the SV algorithm in some detail (chapter 1), and added a roadmap (chapter 2) which describes the actual contributions which are to follow in chapters 3 through 20. Bernhard Scholkopf, Christopher J.C. Burges, Alexander J. Smola Berlin, Holmdel, July 1998/08/25 16:31 1 Introduction to Support Vector Learning The goal of this chapter, which describes the central ideas of SV learning, is twofold. First, we want to provide an introduction for readers unfamiliar with this field. Second, this introduction serves as a source of the basic equations for the chapters of this book. For more exhaustive treatments, we refer the interested reader to Vapnik (1995); Scholkopf (1997); Burges (1998). 1.1
Combining Support Vector and Mathematical . . .
- ADVANCES IN KERNEL METHODS - SUPPORT VECTOR LEARNING
, 1998
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