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Download the fantastic book titled Support Vector Machines written by Ingo Steinwart, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Support Vector Machines", which was released on 15 September 2008. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Support Vector Machines by Ingo Steinwart PDF

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 against several types of model violations and outliers, and last but not least their computational e?ciency compared with several other methods. Although there are several roots and precursors of SVMs, these methods gained particular momentum during the last 15 years since Vapnik (1995, 1998) published his well-known textbooks on statistical learning theory with aspecialemphasisonsupportvectormachines. Sincethen,the?eldofmachine learninghaswitnessedintenseactivityinthestudyofSVMs,whichhasspread moreandmoretootherdisciplinessuchasstatisticsandmathematics. Thusit seems fair to say that several communities are currently working on support vector machines and on related kernel-based methods. Although there are many interactions between these communities, we think that there is still roomforadditionalfruitfulinteractionandwouldbegladifthistextbookwere found helpful in stimulating further research. Many of the results presented in this book have previously been scattered in the journal literature or are still under review. As a consequence, these results have been accessible only to a relativelysmallnumberofspecialists,sometimesprobablyonlytopeoplefrom one community but not the others.


Detail About Support Vector Machines PDF

  • Author : Ingo Steinwart
  • Publisher : Springer Science & Business Media
  • Genre : Computers
  • Total Pages : 611 pages
  • ISBN : 0387772421
  • PDF File Size : 42,6 Mb
  • Language : English
  • Rating : 5/5 from 1 reviews

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Support Vector Machines

Support Vector Machines
  • Publisher : Springer Science & Business Media
  • File Size : 52,6 Mb
  • Release Date : 15 September 2008
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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

Twin Support Vector Machines

Twin Support Vector Machines
  • Publisher : Springer
  • File Size : 52,8 Mb
  • Release Date : 12 October 2016
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This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments for classification and regression. In addition to presenting most

Learning with Kernels

Learning with Kernels
  • Publisher : MIT Press
  • File Size : 49,5 Mb
  • Release Date : 05 June 2018
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A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the

Knowledge Discovery with Support Vector Machines

Knowledge Discovery with Support Vector Machines
  • Publisher : John Wiley & Sons
  • File Size : 39,8 Mb
  • Release Date : 20 September 2011
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An easy-to-follow introduction to support vector machines This book provides an in-depth, easy-to-follow introduction to support vector machines drawing only from minimal, carefully motivated technical and mathematical background material. It

Support Vector Machines Applications

Support Vector Machines Applications
  • Publisher : Springer Science & Business Media
  • File Size : 49,6 Mb
  • Release Date : 12 February 2014
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Support vector machines (SVM) have both a solid mathematical background and practical applications. This book focuses on the recent advances and applications of the SVM, such as image processing, medical

Learning to Classify Text Using Support Vector Machines

Learning to Classify Text Using Support Vector Machines
  • Publisher : Springer Science & Business Media
  • File Size : 30,9 Mb
  • Release Date : 06 December 2012
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Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector Machines presents a new approach to generating text classifiers from examples. The approach combines high

Pattern Recognition with Support Vector Machines

Pattern Recognition with Support Vector Machines
  • Publisher : Springer Science & Business Media
  • File Size : 39,7 Mb
  • Release Date : 29 July 2002
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This book constitutes the refereed proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines, SVM 2002, held in Niagara Falls, Canada in August 2002. The 16 revised full papers

Support Vector Machines

Support Vector Machines
  • Publisher : CRC Press
  • File Size : 24,8 Mb
  • Release Date : 17 December 2012
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Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs)-classification problems and regression problems. The book