63 search results - page 6 / 13 » Learning low-rank kernel matrices |
DAGM
2004
Springer
14 years 2 months ago
2004
Springer
Abstract. During recent years much effort has been spent in incorporating problem specific a-priori knowledge into kernel methods for machine learning. A common example is a-prior...
ML
2006
ACM
13 years 9 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...
JMLR
2006
13 years 9 months ago
2006
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
KDD
2007
ACM
14 years 9 months ago
2007
ACM
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
JMLR
2008
13 years 9 months ago
2008
Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...