19 search results - page 3 / 4 » Regularized linear and kernel redundancy analysis |
CORR
2007
Springer
13 years 6 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...
SDM
2009
SIAM
14 years 3 months ago
2009
SIAM
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
ICASSP
2009
IEEE
13 years 10 months ago
2009
IEEE
In low bit-rate coders, the near-sample and far-sample redundancies of the speech signal are usually removed by a cascade of a shortterm and a long-term linear predictor. These tw...
BMCBI
2010
13 years 3 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...
AAAI
2007
13 years 8 months ago
2007
We propose a novel kernel regression algorithm which takes into account order preferences on unlabeled data. Such preferences have the form that point x1 has a larger target value...