502 search results - page 23 / 101 » Principal Component Analysis for Sparse High-Dimensional Dat... |
CSDA
2008
13 years 8 months ago
2008
A Bayesian approach to analyze the modes of variation in a set of curves is suggested. It is based on a generative model thus allowing for noisy and sparse observations of curves....
BMCBI
2011
13 years 10 days ago
2011
Background: The ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used ...
ITCC
2005
IEEE
14 years 2 months ago
2005
IEEE
We propose a novel, computationally efficient generative topographic model for inferring low dimensional representations of high dimensional data sets, designed to exploit data s...
AAAI
2007
13 years 11 months ago
2007
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
ISNN
2009
Springer
14 years 3 months ago
2009
Springer
Abstract. Nonlinear component analysis is a popular nonlinear feature extraction method. It generally uses eigen-decomposition technique to extract the principal components. But th...