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Support Vector Machines
Steinwart, Ingo; Christmann, Andreas
€ 274.38
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Description for Support Vector Machines
Hardcover. This volume covers all the important topics concerning support vector machines. It provides a unique in-depth treatment of both fundamental and recent material on SVMs that, up to now, has been scattered in the literature. Series: Information Science and Statistics. Num Pages: 617 pages, 10 black & white tables, biography. BIC Classification: UYQM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 241 x 163 x 38. Weight in Grams: 1054.
Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical. David Hilbert The goal of this book is to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety of applications. We try to achieve this by presenting the basic ideas of SVMs together with the latest developments and current research questions in a uni?ed style. In a nutshell, we identify at least three reasons for the success of SVMs: their ability to learn well with only a very small number of free parameters, their robustness ... Read more
Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical. David Hilbert The goal of this book is to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety of applications. We try to achieve this by presenting the basic ideas of SVMs together with the latest developments and current research questions in a uni?ed style. In a nutshell, we identify at least three reasons for the success of SVMs: their ability to learn well with only a very small number of free parameters, their robustness ... Read more
Product Details
Format
Hardback
Publication date
2008
Publisher
Springer-Verlag New York Inc. United States
Number of pages
618
Condition
New
Series
Information Science and Statistics
Number of Pages
603
Place of Publication
New York, NY, United States
ISBN
9780387772417
SKU
V9780387772417
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Steinwart, Ingo; Christmann, Andreas
Ingo Steinwart is a researcher in the machine learning group at the Los Alamos National Laboratory. He works on support vector machines and related methods. Andreas Christmann is Professor of Stochastics in the Department of Mathematics at the University of Bayreuth. He works in particular on support vector machines and robust statistics.
Reviews for Support Vector Machines
From the reviews: “This book has many remarkable qualities which make it commendable to a large mathematical audience. …It is probably the first book on this topic…which is genuinely aimed at a mathematician reader. No technical issue is avoided, and fine points like measurability, integrability, existence and regularity of solutions, etc., are addressed with due rigor and precision. …The ... Read more