66 search results - page 7 / 14 » Mixture Density Mercer Kernels: A Method to Learn Kernels Di... |
PAMI
2007
13 years 7 months ago
2007
The mean-shift algorithm, based on ideas proposed by Fukunaga and Hostetler (1975), is a hill-climbing algorithm on the density defined by a finite mixture or a kernel density e...
IJCNN
2007
IEEE
14 years 2 months ago
2007
IEEE
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
CIDM
2007
IEEE
13 years 11 months ago
2007
IEEE
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
ISNN
2007
Springer
14 years 1 months ago
2007
Springer
Manifold learning algorithms have been proven to be capable of discovering some nonlinear structures. However, it is hard for them to extend to test set directly. In this paper, a ...
NIPS
2007
13 years 9 months ago
2007
A method is proposed for semiparametric estimation where parametric and nonparametric criteria are exploited in density estimation and unsupervised learning. This is accomplished ...