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Paperback. Condition: Very Good. Ex-library paperback in very nice condition with the usual markings and attachments. Text block clean and unmarked. Tight binding.
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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
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Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition)
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Add to basketHardcover. Condition: Fine. No Jacket. 1st Edition. 2006.Hardcover.Fine.343 pages.Ships from Japan.Usually ships in 1-2 working days.
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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
Published by Springer Berlin Heidelberg, 2002
ISBN 10: 354044016X ISBN 13: 9783540440161
Language: English
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Add to basketTaschenbuch. Condition: 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.
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Pattern Recognition with Support Vector Machines
Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg Jul 2002, 2002
ISBN 10: 354044016X ISBN 13: 9783540440161
Language: English
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Add to basketTaschenbuch. Condition: Neu. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 438 pp. Englisch.
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Regularization, Optimization, Kernels, and Support Vector Machines (Chapman & Hall/Crc Machine Learning & Pattern Recognition Series)
Published by Chapman and Hall/CRC 2014-11-14, 2014
ISBN 10: 1482241390 ISBN 13: 9781482241396
Language: English
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Regularization, Optimization, Kernels, and Support Vector Machines (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
Published by Chapman and Hall/CRC, 2014
ISBN 10: 1482241390 ISBN 13: 9781482241396
Language: English
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Regularization, Optimization, Kernels, and Support Vector Machines (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
Published by Chapman and Hall/CRC, 2014
ISBN 10: 1482241390 ISBN 13: 9781482241396
Language: English
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Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition)
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Regularization, Optimization, Kernels, and Support Vector Machines (Chapman & Hall/Crc Machine Learning & Pattern Recognition Series)
Published by Chapman and Hall/CRC, 2014
ISBN 10: 1482241390 ISBN 13: 9781482241396
Language: English
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Support Vector Machines for Pattern Classification (Advances in Computer Vision and Pattern Recognition)
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Pattern Recognition with Support Vector Machines
Published by Springer Berlin Heidelberg Jul 2002, 2002
ISBN 10: 354044016X ISBN 13: 9783540440161
Language: English
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Add to basketTaschenbuch. Condition: 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.
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Pattern Recognition with Support Vector Machines
Published by Springer Berlin Heidelberg, 2002
ISBN 10: 354044016X ISBN 13: 9783540440161
Language: English
US$ 58.27
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Add to basketCondition: 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.
