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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://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.9362
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): 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 a linear decision surface is constructed.
http://scholar.google.com/citations?user=vtegaJgAAAAJ&hl=en
Support-vector networks. C Cortes, V Vapnik. Machine learning 20 (3), 273-297, 1995. 39033: 1995: A training algorithm for optimal margin classifiers. BE Boser, IM Guyon, VN Vapnik. Proceedings of the fifth annual workshop on Computational learning theory ...
https://www.scirp.org/reference/ReferencesPapers.aspx?ReferenceID=2235455
Cortes, C. and Vapnik, V. (1995) Support-Vector Networks. Machine Learning, 20, 273-297. ... C. and Vapnik, V. (1995) Support-Vector Networks. Machine Learning, 20, 273-297. ... many researchers have used support vector regression (SVR) quite successfully to conquer this challenge. In this paper, an SVR based forecasting model is proposed which ...
https://en.wikipedia.org/wiki/Vapnik
Vladimir Naumovich Vapnik (Russian: Владимир Наумович Вапник; born 6 December 1936) is one of the main developers of the Vapnik–Chervonenkis theory of statistical learning, and the co-inventor of the support-vector machine method, and support-vector clustering algorithm.Alma mater: Institute of Control Sciences, …
http://homepages.rpi.edu/~bennek/class/mmld/papers/svn.pdf
output from the 4 hidden units weights of the 4 hidden units dot−products weights of the 5 hidden units dot−products dot−product perceptron output
https://dl.acm.org/doi/10.1023/A%3A1022627411411
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 a linear decision surface is constructed.Author: CortesCorinna, VapnikVladimir
http://www.sciepub.com/reference/47107
Cortes, C. and Vapnik, V., “Support-Vector Networks, ... This research aims to assess and compare performance of single and ensemble classifiers of Support Vector Machine (SVM) and Classification Tree (CT) by using simulation data. The simulation data is based on three data structures which are linearly separable, linearly nonseparable and ...
http://helios.mi.parisdescartes.fr/~bouzy/Doc/AA1/CortesVapnik-SupportVectorNetworks-ML1995.pdf
Support-vector networks Reference • These slides present the following paper: – C.Cortes, V.Vapnik, « support vector networks », Machine Learning (1995) • They are commented with my personal view to teach the key ideas of SVN. • The outline mostly follows the outline of the paper.
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