1051 search results - page 1 / 211 » An algorithm for the principal component analysis of large d... |
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Recently popularized randomized methods for principal component analysis (PCA) efficiently and reliably produce nearly optimal accuracy -- even on parallel processors -- unlike the...
ISNN
2009
Springer
14 years 1 months ago
2009
Springer
Abstract. Nonlinear component analysis is a popular nonlinear feature extraction method. It generally uses eigen-decomposition technique to extract the principal components. But th...
APPT
2005
Springer
14 years 18 days ago
2005
Springer
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...
GLOBECOM
2009
IEEE
14 years 1 months ago
2009
IEEE
—In this paper we look at the problem of accurately reconstructing distributed signals through the collection of a small number of samples at a data gathering point. The techniqu...
ECML
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...