206 search results - page 3 / 42 » Boosting Kernel Models for Regression |
IJON
2007
13 years 5 months ago
2007
In this paper, a ridgelet kernel regression model is proposed for approximation of high dimensional functions. It is based on ridgelet theory, kernel and regularization technology ...
ICCV
2007
IEEE
14 years 7 months ago
2007
IEEE
Discriminative methods for visual object category recognition are typically non-probabilistic, predicting class labels but not directly providing an estimate of uncertainty. Gauss...
IJCNN
2008
IEEE
13 years 11 months ago
2008
IEEE
— A novel sparse kernel density estimator is derived based on a regression approach, which selects a very small subset of significant kernels by means of the D-optimality experi...
ICML
2004
IEEE
14 years 6 months ago
2004
IEEE
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...
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 ...