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- catalog abstract "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.".
- catalog contributor b12620215.
- catalog contributor b12620216.
- catalog contributor b12620217.
- catalog created "c2002.".
- catalog date "2002".
- catalog date "c2002.".
- catalog dateCopyrighted "c2002.".
- catalog description "Includes bibliographical references and index.".
- catalog description "Predicting Signal Peptides with Support Vector Machines / Neelanjan Mukherjee and Sayan Mukherjee -- Scaling Large Learning Problems with Hard Parallel Mixtures / Ronan Collobert, Yoshua Bengio and Samy Bengio -- On the Generalization of Kernel Machines / Pablo Navarrete and Javier Ruiz del Solar -- Kernel Whitening for One-Class Classification / David M.J. Tax and Piotr Juszczak -- A Fast SVM Training Algorithm / Jian-xiong Dong, Adam Krzyzak and Ching Y. Suen -- Support Vector Machines with Embedded Reject Option / Giorgio Fumera and Fabio Roli -- Image Kernels / Annalisa Barla, Emanuele Franceschi, Francesca Odone and Alessandro Verri.".
- catalog description "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.".
- catalog extent "xi, 420 p. :".
- catalog hasFormat "Also available via the World Wide Web.".
- catalog identifier "354044016X (softcover : alk. paper)".
- catalog isFormatOf "Also available via the World Wide Web.".
- catalog isPartOf "Lecture notes in computer science ; 2388".
- catalog issued "2002".
- catalog issued "c2002.".
- catalog language "eng".
- catalog publisher "Berlin ; New York : Springer,".
- catalog relation "Also available via the World Wide Web.".
- catalog subject "006.4 21".
- catalog subject "Artificial intelligence.".
- catalog subject "Computer science.".
- catalog subject "Computer software.".
- catalog subject "Computer vision.".
- catalog subject "Machine learning Congresses.".
- catalog subject "Mathematical statistics.".
- catalog subject "Optical pattern recognition.".
- catalog subject "Pattern recognition systems Congresses.".
- catalog subject "Support vector machines Congresses.".
- catalog subject "TK7882.P3 S86 2002".
- catalog tableOfContents "Predicting Signal Peptides with Support Vector Machines / Neelanjan Mukherjee and Sayan Mukherjee -- Scaling Large Learning Problems with Hard Parallel Mixtures / Ronan Collobert, Yoshua Bengio and Samy Bengio -- On the Generalization of Kernel Machines / Pablo Navarrete and Javier Ruiz del Solar -- Kernel Whitening for One-Class Classification / David M.J. Tax and Piotr Juszczak -- A Fast SVM Training Algorithm / Jian-xiong Dong, Adam Krzyzak and Ching Y. Suen -- Support Vector Machines with Embedded Reject Option / Giorgio Fumera and Fabio Roli -- Image Kernels / Annalisa Barla, Emanuele Franceschi, Francesca Odone and Alessandro Verri.".
- catalog title "Pattern recognition with support vector machines : first international workshop, SVM 2002, Niagara Falls, Canada, August 10, 2002 : proceedings / Seong-Whan Lee, Alessandro Verri (eds.).".
- catalog type "Conference proceedings. fast".
- catalog type "text".