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» A novel SVM Geometric Algorithm based on Reduced Convex Hull...
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ICPR
2006
IEEE
14 years 5 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 atte...
Michael E. Mavroforakis, Margaritis Sdralis, Sergi...
ICML
2000
IEEE
14 years 5 months ago
Duality and Geometry in SVM Classifiers
We develop an intuitive geometric interpretation of the standard support vector machine (SVM) for classification of both linearly separable and inseparable data and provide a rigo...
Kristin P. Bennett, Erin J. Bredensteiner
ICPR
2010
IEEE
13 years 9 months ago
Large Margin Classifier Based on Affine Hulls
This paper introduces a geometrically inspired large-margin classifier that can be a better alternative to the Support Vector Machines (SVMs) for the classification problems with ...
Hakan Cevikalp, Hasan Serhan Yavuz
CVPR
2010
IEEE
13 years 10 months ago
Face Recognition Based on Image Sets
We introduce a novel method for face recognition from image sets. In our setting each test and training example is a set of images of an individual’s face, not just a single ima...
Hakan Cevikalp, Bill Triggs
ICML
2004
IEEE
14 years 5 months ago
Multiple kernel learning, conic duality, and the SMO algorithm
While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. ...
Francis R. Bach, Gert R. G. Lanckriet, Michael I. ...