1051 search results - page 1 / 211 » An algorithm for the principal component analysis of large d... |
68
Voted
CORR
2010
Springer
14 years 10 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...
109
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ISNN
2009
Springer
15 years 4 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
15 years 3 months 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
15 years 4 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...
110
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ECML
2007
Springer
15 years 4 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...