229 search results - page 4 / 46 » Image Classification Using Marginalized Kernels for Graphs |
PKDD
2010
Springer
13 years 6 months ago
2010
Springer
Abstract. The eigenspectrum of a graph Laplacian encodes smoothness information over the graph. A natural approach to learning involves transforming the spectrum of a graph Laplaci...
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) ...
CLEF
2010
Springer
13 years 8 months ago
2010
Springer
This paper describes the participation of Idiap-MULTI to the Robot Vision Task at imageCLEF 2010. Our approach was based on a discriminative classification algorithm using multiple...
CORR
2008
Springer
13 years 7 months ago
2008
Springer
Graph kernels methods are based on an implicit embedding of graphs within a vector space of large dimension. This implicit embedding allows to apply to graphs methods which where u...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
Structural alignments are the most widely used tools for comparing proteins with low sequence similarity. The main contribution of this paper is to derive various kernels on prote...