545 search results - page 25 / 109 » Support Vector Regression Using Mahalanobis Kernels |
185
Voted
JMLR
2011
15 years 1 months ago
2011
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
206
Voted
FLAIRS
2004
15 years 7 months ago
2004
One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
187
Voted
COLT
2007
Springer
16 years 17 days ago
2007
Springer
In the multi-view regression problem, we have a regression problem where the input variable (which is a real vector) can be partitioned into two different views, where it is assum...
196
Voted
COLT
1999
Springer
15 years 10 months ago
1999
Springer
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
183
Voted
CVPR
2004
IEEE
15 years 10 months ago
2004
IEEE
Relevance feedback approaches based on support vector machine (SVM) learning have been applied to significantly improve retrieval performance in content-based image retrieval (CBI...