12 search results - page 1 / 3 » Multi-task feature and kernel selection for SVMs |
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
We compute a common feature selection or kernel selection configuration for multiple support vector machines (SVMs) trained on different yet inter-related datasets. The method is ...
ECCV
2008
Springer
14 years 6 months ago
2008
Springer
Abstract. We address the problem of estimating human body pose from a single image with cluttered background. We train multiple local linear regressors for estimating the 3D pose f...
CORR
2006
Springer
13 years 4 months ago
2006
Springer
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
EMNLP
2009
13 years 2 months ago
2009
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
ESANN
2006
13 years 5 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 ...