166 search results - page 12 / 34 » Learning a kernel matrix for nonlinear dimensionality reduct... |
NIPS
2008
13 years 10 months ago
2008
In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representa...
ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
ICMLC
2005
Springer
14 years 2 months ago
2005
Springer
Abstract. Many supervised and unsupervised learning algorithms depend on the choice of an appropriate distance metric. While metric learning for supervised learning tasks has a lon...
BMCBI
2010
13 years 6 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...
ICCV
2009
IEEE
15 years 1 months ago
2009
IEEE
We propose an unconventional but highly effective approach
to robust fitting of multiple structures by using statistical
learning concepts. We design a novel Mercer kernel
for t...