267 search results - page 7 / 54 » Ridgelet kernel regression |
BMCBI
2010
13 years 5 months ago
2010
Background: Most genomic data have ultra-high dimensions with more than 10,000 genes (probes). Regularization methods with L1 and Lp penalty have been extensively studied in survi...
ANNPR
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. In our previous work we have shown that Mahalanobis kernels are useful for support vector classifiers both from generalization ability and model selection speed. In this ...
ECAI
2010
Springer
13 years 5 months ago
2010
Springer
The proposed feature selection method aims to find a minimum subset of the most informative variables for classification/regression by efficiently approximating the Markov Blanket ...
NIPS
2008
13 years 9 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
DAGM
2008
Springer
13 years 9 months ago
2008
Springer
Abstract. This paper proposes a regression-based method for singleimage super-resolution. Kernel ridge regression (KRR) is used to estimate the high-frequency details of the underl...