93 search results - page 4 / 19 » Supervised probabilistic principal component analysis |
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Principal components and canonical correlations are at the root of many exploratory data mining techniques and provide standard pre-processing tools in machine learning. Lately, p...
FGR
2004
IEEE
13 years 11 months ago
2004
IEEE
Intra-personal space modeling proposed by Moghaddam et. al. has been successfully applied in face recognition. In their work the regular principal subspaces are derived from the i...
ADBIS
2003
Springer
14 years 28 days ago
2003
Springer
Recent research has shown the integration of multiple classifiers to be one of the most important directions in machine learning and data mining. It was shown that, for an ensemble...
JMLR
2010
13 years 2 months ago
2010
Bayesian principal component analysis (BPCA), a probabilistic reformulation of PCA with Bayesian model selection, is a systematic approach to determining the number of essential p...
NIPS
2003
13 years 9 months ago
2003
Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...