40 search results - page 3 / 8 » Kernel Feature Selection with Side Data Using a Spectral App... |
ICPR
2006
IEEE
14 years 6 months ago
2006
IEEE
In this paper, a novel unsupervised approach for the segmentation of unorganized 3D points sets is proposed. The method derives by the mean shift clustering paradigm devoted to se...
ESANN
2006
13 years 6 months ago
2006
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
CVPR
2010
IEEE
13 years 9 months ago
2010
IEEE
Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the original...
ESANN
2008
13 years 6 months ago
2008
This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental ...
CORR
2008
Springer
13 years 5 months ago
2008
Springer
: Applications such as Face Recognition (FR) that deal with high-dimensional data need a mapping technique that introduces representation of low-dimensional features with enhanced ...