22 search results - page 3 / 5 » Deblurring Using Regularized Locally Adaptive Kernel Regress... |
CVPR
2007
IEEE
13 years 11 months ago
2007
IEEE
This paper describes a local ensemble kernel learning technique to recognize/classify objects from a large number of diverse categories. Due to the possibly large intraclass featu...
CORR
2007
Springer
13 years 4 months ago
2007
Springer
We consider the least-square regression problem with regularization by a block 1-norm, that is, a sum of Euclidean norms over spaces of dimensions larger than one. This problem, r...
BMCBI
2010
13 years 2 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...
PAMI
2010
13 years 3 months ago
2010
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
ECML
2005
Springer
13 years 10 months ago
2005
Springer
ABSTRACT. Estimating a non-uniformly sampled function from a set of learning points is a classical regression problem. Kernel methods have been widely used in this context, but eve...