1051 search results - page 15 / 211 » An algorithm for the principal component analysis of large d... |
IDEAL
2005
Springer
14 years 1 months ago
2005
Springer
Abstract. Normal mixture models are often used to cluster continuous data. However, conventional approaches for fitting these models will have problems in producing nonsingular es...
CIKM
2010
Springer
13 years 6 months ago
2010
Springer
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
ISBI
2007
IEEE
14 years 2 months ago
2007
IEEE
Statistical shape analysis techniques commonly employed in the medical imaging community, such as Active Shape Models or Active Appearance Models, rely on Principal Component Anal...
ICML
2004
IEEE
14 years 8 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 ...
IDEAL
2003
Springer
14 years 1 months ago
2003
Springer
Abstract. Multidimensional data projection and visualisation are becoming increasingly important and have found wide applications in many fields such as decision support, bioinform...