910 search results - page 3 / 182 » Progressive Principal Component Analysis |
AAAI
2004
13 years 9 months ago
2004
Based on the probabilistic reformulation of principal component analysis (PCA), we consider the problem of determining the number of principal components as a model selection prob...
IGARSS
2009
13 years 5 months ago
2009
Kernel Principal Component Analysis (KPCA) is investigated for feature extraction from hyperspectral remotesensing data. Features extracted using KPCA are used to construct the Ex...
ICIAR
2004
Springer
14 years 27 days ago
2004
Springer
SAS
2010
Springer
13 years 6 months ago
2010
Springer
Numerical Abstract Domains via Principal Component Analysis Gianluca Amato, Maurizio Parton, and Francesca Scozzari Universit`a di Chieti-Pescara – Dipartimento di Scienze We pro...
ICONIP
2007
13 years 9 months ago
2007
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...