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ICPR
2006
IEEE

A novel SVM Geometric Algorithm based on Reduced Convex Hulls

14 years 4 months ago
A novel SVM Geometric Algorithm based on Reduced Convex Hulls
Geometric methods are very intuitive and provide a theoretically solid viewpoint to many optimization problems. SVM is a typical optimization task that has attracted a lot of attention over the recent years in many Pattern Recognition and Machine Learning tasks. In this work, we exploit recent results in Reduced Convex Hulls (RCH) and apply them to a Nearest Point Algorithm (NPA) leading to an elegant and efficient solution to the general (linear and nonlinear, separable and non-separable) SVM classification task.
Michael E. Mavroforakis, Margaritis Sdralis, Sergi
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2006
Where ICPR
Authors Michael E. Mavroforakis, Margaritis Sdralis, Sergios Theodoridis
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