5131 search results - page 71 / 1027 » Heterogeneous Component Analysis |
COLT
2004
Springer
14 years 2 months ago
2004
Springer
The main goal of this paper is to prove inequalities on the reconstruction error for Kernel Principal Component Analysis. With respect to previous work on this topic, our contribu...
NIPS
2008
13 years 10 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
IJON
2006
13 years 9 months ago
2006
We present an application of Independent Component Analysis (ICA) to the discrimination of mental tasks for EEG-based Brain Computer Interface systems. ICA is most commonly used w...
PAMI
2008
13 years 9 months ago
2008
In data-analysis problems with a large number of dimension, principal component analysis based on L2-norm (L2PCA) is one of the most popular methods, but L2-PCA is sensitive to out...
IJON
2007
13 years 8 months ago
2007
In this paper we present a method of parameter optimization, relative trust-region learning, where the trust-region method and the relative optimization [21] are jointly exploited...