178 search results - page 14 / 36 » Extensions of Manifold Learning Algorithms in Kernel Feature... |
KAIS
2007
13 years 7 months ago
2007
With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive ...
ML
2006
ACM
13 years 7 months ago
2006
ACM
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
CVPR
2010
IEEE
13 years 12 months ago
2010
IEEE
Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the original...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...