543 search results - page 6 / 109 » Nonlinear principal component analysis of noisy data |
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...
BMCBI
2010
13 years 7 months ago
2010
Background: Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique fo...
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...
DATASCIENCE
2002
13 years 7 months ago
2002
The relationship between apparently disparate sets of data is a critical component of interpreting materials' behavior, especially in terms of assessing the impact of the mic...
COLT
2010
Springer
13 years 5 months ago
2010
Springer
We consider the dimensionality-reduction problem (finding a subspace approximation of observed data) for contaminated data in the high dimensional regime, where the number of obse...