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Pattern Recognition with Support Vector Machines: First International Workshop, SVM 2002, Niagara Falls, Canada, August 10, 2002. Proceedings: 2388 (Lecture Notes in Computer Science) - Softcover
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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.
Reseña del editor
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 and 14 poster papers presented together with two invited contributions were carefully reviewed and selected from 57 full paper submissions. The papers presented span the whole range of topics in pattern recognition with support vector machines from computational theories to implementations and applications.
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- VerlagSpringer
- Erscheinungsdatum2008
- ISBN 10 354044016X
- ISBN 13 9783540440161
- EinbandTapa blanda
- SpracheEnglisch
- Anzahl der Seiten440
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Pattern Recognition with Support Vector Machines: First International Workshop, SVM 2002, Niagara Falls, Canada, August 10, 2002. Proceedings (Lecture Notes in Computer Science)
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Pattern Recognition with Support Vector Machines: First International Workshop, SVM 2002, Niagara Falls, Canada, August 10, 2002. Proceedings (Lecture Notes in Computer Science, 2388)
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Pattern Recognition with Support Vector Machines: First International Workshop, SVM 2002, Niagara Falls, Canada, August 10, 2002. Proceedings (Lecture Notes in Computer Science, 2388)
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Pattern Recognition with Support Vector Machines
Verlag:
Springer Berlin Heidelberg Jul 2002, 2002
ISBN 10: 354044016X
ISBN 13: 9783540440161
Neu
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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,th e 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. 438 pp. Englisch. Bestandsnummer des Verkäufers 9783540440161
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Pattern Recognition With Support Vector Machines : First International Workshop, Svm 2002, Niagara Falls, Canada, August 10, 2002 : Proceedings
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Pattern Recognition With Support Vector Machines : First International Workshop, Svm 2002, Niagara Falls, Canada, August 10, 2002 : Proceedings
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Pattern Recognition with Support Vector Machines : First International Workshop, SVM 2002, Niagara Falls, Canada, August 10, 2002. Proceedings
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9783540440161
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Pattern Recognition with Support Vector Machines
Verlag:
Springer Berlin Heidelberg, 2002
ISBN 10: 354044016X
ISBN 13: 9783540440161
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Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Invited Papers.- Predicting Signal Peptides with Support Vector Machines.- Scaling Large Learning Problems with Hard Parallel Mixtures.- Computational Issues.- On the Generalization of Kernel Machines.- Kernel Whitening for One-Class Classification.- A Fast. Bestandsnummer des Verkäufers 4890790
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