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» Data selection for support vector machine classifiers
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ICML
2003
IEEE
15 years 10 months ago
Discriminative Gaussian Mixture Models: A Comparison with Kernel Classifiers
We show that a classifier based on Gaussian mixture models (GMM) can be trained discriminatively to improve accuracy. We describe a training procedure based on the extended Baum-W...
Aldebaro Klautau, Nikola Jevtic, Alon Orlitsky
ESANN
2000
14 years 11 months ago
Algorithmic approaches to training Support Vector Machines: a survey
: Support Vector Machines (SVMs) have become an increasingly popular tool for machine learning tasks involving classi cation, regression or novelty detection. They exhibit good gen...
Colin Campbell
JMLR
2008
116views more  JMLR 2008»
14 years 9 months ago
Support Vector Machinery for Infinite Ensemble Learning
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
Hsuan-Tien Lin, Ling Li
CVPR
2001
IEEE
15 years 11 months ago
A New 3-D Pattern Recognition Technique With Application to Computer Aided Colonoscopy
To utilize CT or MRI images for computer aided diagnosis applications, robust features that represent 3-D image data need to be constructed and subsequently used by a classificati...
Salih Burak Göktürk, Carlo Tomasi
ICML
2006
IEEE
15 years 10 months ago
Permutation invariant SVMs
We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...
Pannagadatta K. Shivaswamy, Tony Jebara