502 search results - page 23 / 101 » Principal Component Analysis for Sparse High-Dimensional Dat... |
100
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CSDA
2008
15 years 16 days 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....
161
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BMCBI
2011
14 years 4 months 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 ...
101
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ITCC
2005
IEEE
15 years 6 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...
103
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AAAI
2007
15 years 2 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...
136
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ISNN
2009
Springer
15 years 7 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...