68 search results - page 9 / 14 » The Use of Bayesian Framework for Kernel Selection in Vector... |
KDD
2008
ACM
14 years 8 months ago
2008
ACM
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
JMLR
2002
13 years 8 months ago
2002
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
ECML
2006
Springer
14 years 3 days ago
2006
Springer
Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
ICPR
2008
IEEE
14 years 9 months ago
2008
IEEE
The aim of this study is to apply a state-of-the-art speech emotion recognition engine on the detection of microsleep endangered sleepiness states. Current approaches in speech em...
Book
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...