175 search results - page 3 / 35 » A DC-programming algorithm for kernel selection |
ICML
2004
IEEE
14 years 7 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...
JISE
2010
13 years 1 months ago
2010
In dealing with large datasets the reduced support vector machine (RSVM) was proposed for the practical objective to overcome the computational difficulties as well as to reduce t...
MCS
2010
Springer
13 years 4 months ago
2010
Springer
Abstract. The Support Kernel Machine (SKM) and the Relevance Kernel Machine (RKM) are two principles for selectively combining objectrepresentation modalities of different kinds b...
IJCNN
2008
IEEE
14 years 23 days 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
2008
IEEE
14 years 7 months ago
2008
IEEE
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...