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IJCNN
2006
IEEE
14 years 1 months ago
Learning the Kernel in Mahalanobis One-Class Support Vector Machines
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
Ivor W. Tsang, James T. Kwok, Shutao Li
IBPRIA
2009
Springer
13 years 5 months ago
Real-Time Motion Detection for a Mobile Observer Using Multiple Kernel Tracking and Belief Propagation
We propose a novel statistical method for motion detection and background maintenance for a mobile observer. Our method is based on global motion estimation and statistical backgro...
Marc Vivet, Brais Martínez, Xavier Binefa
ICRA
2009
IEEE
175views Robotics» more  ICRA 2009»
13 years 5 months ago
A combination of particle filtering and deterministic approaches for multiple kernel tracking
Color-based tracking methods have proved to be efficient for their robustness qualities. The drawback of such global representation of an object is the lack of information on its s...
Céline Teuliere, Éric Marchand, Laur...
JMLR
2010
151views more  JMLR 2010»
13 years 2 months ago
The Feature Selection Path in Kernel Methods
The problem of automatic feature selection/weighting in kernel methods is examined. We work on a formulation that optimizes both the weights of features and the parameters of the ...
Fuxin Li, Cristian Sminchisescu
DCC
2009
IEEE
14 years 8 months ago
Compressed Kernel Perceptrons
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
Slobodan Vucetic, Vladimir Coric, Zhuang Wang