12 search results - page 1 / 3 » Automated hierarchical mixtures of probabilistic principal c... |
ICML
2004
IEEE
14 years 6 months ago
2004
IEEE
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
ESANN
2007
13 years 6 months ago
2007
Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to...
IEICET
2010
13 years 3 months ago
2010
Estimating the ratio of two probability density functions (a.k.a. the importance) has recently gathered a great deal of attention since importance estimators can be used for solvi...
ICASSP
2010
IEEE
13 years 5 months ago
2010
IEEE
The importance estimation problem (estimating the ratio of two probability density functions) has recently gathered a great deal of attention for use in various applications, e.g....
BMCBI
2010
13 years 4 months ago
2010
Background: Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique fo...