With their introduction in 1995, Support Vector Machines (SVMs) marked the beginningofanewerainthelearningfromexamplesparadigm.Rootedinthe Statistical Learning Theory developed by Vladimir Vapnik at AT&T, SVMs quickly gained attention from the pattern recognition community due to a n- beroftheoreticalandcomputationalmerits.Theseinclude, forexample, the simple geometrical interpretation of the margin, uniqueness of the solution, s- tistical robustness of the loss function, modularity of the kernel function, and over't control through the choice of a single regularization parameter.
Author(s): Seong-Whan Lee & Alessandro Verri
428 Pages
Computers, Optical Data Processing
Series Name: Lecture Notes in Computer Science
Description
Book Synopsis
With their introduction in 1995, Support Vector Machines (SVMs) marked the beginningofanewerainthelearningfromexamplesparadigm.Rootedinthe Statistical Learning Theory developed by Vladimir Vapnik at AT&T, SVMs quickly gained attention from the pattern recognition community due to a n- beroftheoreticalandcomputationalmerits.Theseinclude, forexample, the simple geometrical interpretation of the margin, uniqueness of the solution, s- tistical robustness of the loss function, modularity of the kernel function, and over't control through the choice of a single regularization parameter. Like all really good and far reaching ideas, SVMs raised a number of - terestingproblemsforboththeoreticiansandpractitioners.Newapproachesto Statistical Learning Theory are under development and new and more e?cient methods for computing SVM with a large number of examples are being studied. Being interested in the development of trainable systems ourselves, we decided to organize an international workshop as a satellite event of the 16th Inter- tional Conference on Pattern Recognition emphasizing the practical impact and relevance of SVMs for pattern recognition. By March 2002, a total of 57 full papers had been submitted from 21 co- tries.Toensurethehighqualityofworkshopandproceedings, theprogramc- mitteeselectedandaccepted30ofthemafterathoroughreviewprocess.Ofthese papers16werepresentedin4oralsessionsand14inapostersession.Thepapers span a variety of topics in pattern recognition with SVMs from computational theoriestotheirimplementations.Inadditiontotheseexcellentpresentations, there were two invited papers by Sayan Mukherjee, MIT and Yoshua Bengio, University of Montreal.
Dimensions (Overall): 9.3 Inches (H) x 6.22 Inches (W) x .68 Inches (D)
Weight: 1.39 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 428
Genre: Computers
Sub-Genre: Optical Data Processing
Series Title: Lecture Notes in Computer Science
Publisher: Springer
Format: Paperback
Author: Seong-Whan Lee & Alessandro Verri
Language: English
Street Date: July 29, 2002
TCIN: 1011231212
UPC: 9783540440161
Item Number (DPCI): 247-05-3873
Origin: Made in the USA or Imported
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