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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
http://web.cecs.pdx.edu/~mm/AIFall2011/SVMs.pdf
Support Vector Machines (Vapnik, 1979) • Assume a binary classification problem. ... support vectors and coefficients also depends only on dot products between training examples, rather than on the training examples outside of dot products. – So if each x i
http://scholar.google.com/citations?user=vtegaJgAAAAJ&hl=en
Support vector machines for histogram-based image classification. O Chapelle, P Haffner, VN Vapnik. IEEE transactions on Neural Networks 10 (5), 1055 ... M Pontil, T Poggio, V Vapnik. Advances in neural information processing systems, 668-674, 2001. 1277: 2001: Pattern recognition using generalized portrait method. V Vapnik. Automation and ...
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
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 ...
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