545 search results - page 25 / 109 » Support Vector Regression Using Mahalanobis Kernels |
128
Voted
JMLR
2011
14 years 9 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...
150
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FLAIRS
2004
15 years 3 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...
132
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COLT
2007
Springer
15 years 8 months 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...
141
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COLT
1999
Springer
15 years 6 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...
131
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CVPR
2004
IEEE
15 years 6 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...