28 search results - page 5 / 6 » Reproducing kernel Hilbert spaces for spike train analysis |
TNN
2011
13 years 2 months ago
2011
Domain adaptation solves a learning problem in a target domain by utilizing the training data in a different but related source domain. Intuitively, discovering a good feature rep...
NIPS
2001
13 years 9 months ago
2001
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
TSP
2008
13 years 7 months ago
2008
The combination of the famed kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample by sample update for an adaptive filter in reproducing Kernel Hil...
JCP
2008
13 years 7 months ago
2008
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
CORR
2007
Springer
13 years 7 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...