28 search results - page 4 / 6 » Post-nonlinear Independent Component Analysis by Variational... |
IDA
2009
Springer
13 years 12 months ago
2009
Springer
Abstract. We present a probabilistic model for robust principal component analysis (PCA) in which the observation noise is modelled by Student-t distributions that are independent ...
JMLR
2010
13 years 5 days ago
2010
Principal component analysis (PCA) is a classical data analysis technique that finds linear transformations of data that retain the maximal amount of variance. We study a case whe...
IDA
2009
Springer
13 years 12 months ago
2009
Springer
Abstract. Binary Factor Analysis (BFA) is a typical problem of Independent Component Analysis (ICA) where the signal sources are binary. Parameter learning and model selection in B...
BMCBI
2006
13 years 5 months ago
2006
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
TMI
2010
13 years 3 months ago
2010
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...