318 search results - page 34 / 64 » Learning subspace kernels for classification |
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
A new kernel function between two labeled graphs is presented. Feature vectors are defined as the counts of label paths produced by random walks on graphs. The kernel computation ...
GCB
2009
Springer
13 years 11 months ago
2009
Springer
Abstract: Graphs are often used to describe and analyze the geometry and physicochemical composition of biomolecular structures, such as chemical compounds and protein active sites...
BMCBI
2010
13 years 7 months ago
2010
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
TNN
2010
13 years 2 months ago
2010
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
For large-scale classification problems, the training samples can be clustered beforehand as a downsampling pre-process, and then only the obtained clusters are used for training....