156 search results - page 6 / 32 » Generalized Principal Component Analysis (GPCA) |
NIPS
1993
13 years 8 months ago
1993
We present a new algorithm for eliminating excess parameters and improving network generalization after supervised training. The method, \Principal Components Pruning (PCP)",...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
CIKM
2010
Springer
13 years 6 months ago
2010
Springer
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
— We introduce in this paper methods for finding mutually corresponding dependent components from two different but related data sets in an unsupervised (blind) manner. The basi...
IJCNN
2007
IEEE
14 years 1 months ago
2007
IEEE
— To approximate complex data, we propose new type of low-dimensional “principal object”: principal cubic complex. This complex is a generalization of linear and nonlinear pr...