Pattern Recognition Support Vector (32 results)
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Pattern Recognition With Support Vector Machines : First International Workshop, Svm 2002, Niagara Falls, Canada, August 10, 2002 : Proceedings
Svm 200 (2002 Niagara Falls, Ont.); Verri, Alessandro (EDT); Lee, Seong-Whan (EDT)
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Paperback or Softback. Condition: New. Pattern Recognition with Support Vector Machines: First International Workshop, Svm 2002, Niagara Falls, Canada, August 10, 2002. Proceedings. Book.
Pattern Recognition With Support Vector Machines : First International Workshop, Svm 2002, Niagara Falls, Canada, August 10, 2002 : Proceedings
Svm 200 (2002 Niagara Falls, Ont.); Verri, Alessandro (EDT); Lee, Seong-Whan (EDT)
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Published by Springer-Verlag Berlin and Heidelberg GmbH and Co. KG, DE, 2002
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Paperback. Condition: New. 2002 ed. With their introduction in 1995, Support Vector Machines (SVMs) marked the beginningofanewerainthelearningfromexamplesparadigm.Rootedinthe Statistical Learning Theory developed by Vladimir Vapnik at ATandT, SVMs quickly gained attention from the pattern recognition community due to a n- beroft…heoreticalandcomputationalmerits.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.
Language: English
Published by Chapman and Hall/CRC, 2020
Series: Book 7 of 15 - Chapman & Hall/Crc Machine Learning & Pattern Recognition
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Published by Chapman and Hall/CRC, 2020
Series: Book 7 of 15 - Chapman & Hall/Crc Machine Learning & Pattern Recognition
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Pattern Recognition With Support Vector Machines : First International Workshop, Svm 2002, Niagara Falls, Canada, August 10, 2002 : Proceedings
Svm 200 (2002 Niagara Falls, Ont.); Verri, Alessandro (EDT); Lee, Seong-Whan (EDT)
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Pattern Recognition With Support Vector Machines : First International Workshop, Svm 2002, Niagara Falls, Canada, August 10, 2002 : Proceedings
Svm 200 (2002 Niagara Falls, Ont.); Verri, Alessandro (EDT); Lee, Seong-Whan (EDT)
- Softcover
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Taschenbuch. 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 patt…ern 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.
- Hardcover
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Published by Springer-Verlag Berlin and Heidelberg GmbH and Co. KG, DE, 2002
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Paperback. Condition: New. 2002 ed. With their introduction in 1995, Support Vector Machines (SVMs) marked the beginningofanewerainthelearningfromexamplesparadigm.Rootedinthe Statistical Learning Theory developed by Vladimir Vapnik at ATandT, SVMs quickly gained attention from the pattern recognition community due to a n- beroft…heoreticalandcomputationalmerits.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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Published by Springer, 2010
Series: Book 13 of 86 - Advances in Computer Vision and Pattern Recognition
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Published by Chapman and Hall/CRC, 2014
Series: Book 7 of 15 - Chapman & Hall/Crc Machine Learning & Pattern Recognition
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Published by Chapman and Hall/CRC, 2014
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Published by Springer, 2012
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Taschenbuch. 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 attenti…on 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. 438 pp. Englisch.
Language: English
Published by Chapman and Hall/CRC, 2020
Series: Book 7 of 15 - Chapman & Hall/Crc Machine Learning & Pattern Recognition
- Softcover
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Condition: New. PRINT ON DEMAND pp. 525.
