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CIARP
2010
Springer
15 years 1 months ago
A New Algorithm for Training SVMs Using Approximate Minimal Enclosing Balls
Abstract. It has been shown that many kernel methods can be equivalently formulated as minimal-enclosing-ball (MEB) problems in certain feature space. Exploiting this reduction eff...
Emanuele Frandi, Maria Grazia Gasparo, Stefano Lod...
GBRPR
2009
Springer
15 years 10 months ago
Edition within a Graph Kernel Framework for Shape Recognition
A large family of shape comparison methods is based on a medial axis transform combined with an encoding of the skeleton by a graph. Despite many qualities this encoding of shapes ...
François-Xavier Dupé, Luc Brun
ICASSP
2008
IEEE
15 years 10 months ago
Learning the kernel via convex optimization
The performance of a kernel-based learning algorithm depends very much on the choice of the kernel. Recently, much attention has been paid to the problem of learning the kernel it...
Seung-Jean Kim, Argyrios Zymnis, Alessandro Magnan...
ICPR
2010
IEEE
15 years 9 months ago
2D Shape Recognition Using Information Theoretic Kernels
In this paper, a novel approach for contour-based 2D shape recognition is proposed, using a recently introduced class of information theoretic kernels. This kind of kernels, based...
Manuele Bicego, André Filipe Torres Martins, Vitt...
DIS
2008
Springer
15 years 5 months ago
String Kernels Based on Variable-Length-Don't-Care Patterns
Abstract. We propose a new string kernel based on variable-lengthdon't-care patterns (VLDC patterns). A VLDC pattern is an element of ({}) , where is an alphabet and is the ...
Kazuyuki Narisawa, Hideo Bannai, Kohei Hatano, Shu...