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http://image.diku.dk/imagecanon/material/cortes_vapnik95.pdf
Support-Vector Networks CORINNA CORTES [email protected] VLADIMIR VAPNIK [email protected] AT&T Bell Labs., Holmdel, NJ 07733, USA Editor: Lorenza Saitta Abstract. The support-vector network is a new learning machine for two-group classification problems. The
https://link.springer.com/article/10.1007%2FBF00994018
Sep 01, 1995 · The idea behind the support-vector network was previously implemented for the restricted case where the training data can be separated without errors. We here extend this result to non-separable training data. High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated.Cited by: 38765
http://scholar.google.com/citations?user=vtegaJgAAAAJ&hl=en
Support vector method for function approximation, regression estimation and signal processing V Vapnik, SE Golowich, AJ Smola Advances in neural information processing systems, 281-287 , 1997
https://link.springer.com/article/10.1023%2FA%3A1022627411411
Sep 01, 1995 · The support-vector network is a new learning machine for two-group classification problems. The machine conceptually implements the following idea: input vectors are non-linearly mapped to a very high-dimension feature space. In this feature space …Cited by: 38765
https://datascience.columbia.edu/vladimir-vapnik
Professor Vapnik has taught and researched in computer science, theoretical and applied statistics for over 30 years. ... of a general theory of minimizing the expected risk using empirical data and a new type of learning machine called Support Vector machine that possesses a high level of generalization ability. These techniques have been used ...
https://www.researchgate.net/publication/221621494_Support_Vector_Machines_Theory_and_Applications
This chapter presents a summary of the issues discussed during the one day workshop on ”Support Vector Machines (SVM) Theory and Applications” organized as part of the Advanced Course on ...
https://www.amazon.com/Statistical-Learning-Theory-Vladimir-Vapnik/dp/0471030031
Aug 17, 2015 · The theory has been quite successful at attacking the pattern recognition/ classification problem and provides a basis for understanding support vector machines. However Vapnik sees a much broader application to statistical inference in general when the classical parametric approach fails.5/5(6)
http://www.cs.columbia.edu/~kathy/cs4701/documents/jason_svm_tutorial.pdf
Support Vector Machine (and Statistical Learning Theory) Tutorial Jason Weston NEC Labs America 4 Independence Way, Princeton, USA. [email protected]. 1 Support Vector Machines: history SVMs introduced in COLT-92 by Boser, Guyon & Vapnik. Became rather popular since. Theoretically well motivated algorithm: developed from Statistical
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