95 search results - page 3 / 19 » Core Vector Regression for very large regression problems |
KDD
2002
ACM
14 years 8 months ago
2002
ACM
Recently there has been an increasing interest in developing regression models for large datasets that are both accurate and easy to interpret. Regressors that have these properti...
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
Abstract— This paper considers the basis vector selection issue invloved in forward selection algorithms to sparse Gaussian Process Regression (GPR). Firstly, we re-examine a pre...
IWANN
2005
Springer
14 years 1 months ago
2005
Springer
Based on the Nystr¨om approximation and the primal-dual formulation of Least Squares Support Vector Machines (LS-SVM), it becomes possible to apply a nonlinear model to a large sc...
CORR
2008
Springer
13 years 7 months ago
2008
Springer
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
TNN
2008
13 years 7 months ago
2008
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...