376 search results - page 7 / 76 » Supervised dimensionality reduction using mixture models |
TNN
2008
13 years 9 months ago
2008
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
ESANN
2007
13 years 11 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...
IBPRIA
2003
Springer
14 years 3 months ago
2003
Springer
The dimensionality of the input data often far exceeds their intrinsic dimensionality. As a result, it may be difficult to recognize multidimensional data, especially if the number...
ML
2010
ACM
13 years 8 months ago
2010
ACM
When only a small number of labeled samples are available, supervised dimensionality reduction methods tend to perform poorly due to overfitting. In such cases, unlabeled samples ...
ICPR
2008
IEEE
14 years 11 months ago
2008
IEEE
Facial expression recognition is a topic of interest both in industry and academia. Recent approaches to facial expression recognition are based on mapping expressions to low dime...