325 search results - page 32 / 65 » Statistical Properties of Kernel Principal Component Analysi... |
142
Voted
NIPS
1997
15 years 5 months ago
1997
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
155
Voted
BMCBI
2007
15 years 3 months ago
2007
Background: When analyzing microarray gene expression data, missing values are often encountered. Most multivariate statistical methods proposed for microarray data analysis canno...
108
click to vote
ALT
2005
Springer
16 years 18 days ago
2005
Springer
Abstract. We propose an independence criterion based on the eigenspectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate ...
159
Voted
TNN
2008
15 years 3 months ago
2008
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
116
Voted
IJCNN
2007
IEEE
15 years 10 months ago
2007
IEEE
—In this paper, a new model that can ultimately create its own set of perceptual features is proposed. Using a bidirectional associative memory (BAM)-inspired architecture, the r...