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JMLR
2012
11 years 10 months ago
Sparse Higher-Order Principal Components Analysis
Traditional tensor decompositions such as the CANDECOMP / PARAFAC (CP) and Tucker decompositions yield higher-order principal components that have been used to understand tensor d...
Genevera Allen
ICIP
2008
IEEE
14 years 9 months ago
Principal components for non-local means image denoising
This paper presents an image denoising algorithm that uses principal component analysis (PCA) in conjunction with the non-local means image denoising. Image neighborhood vectors u...
Tolga Tasdizen
BMCBI
2011
12 years 11 months ago
Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and STRUCTU
Background: The ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used ...
Tulaya Limpiti, Apichart Intarapanich, Anunchai As...
BMCBI
2010
146views more  BMCBI 2010»
13 years 7 months ago
Nonnegative principal component analysis for mass spectral serum profiles and biomarker discovery
Background: As a novel cancer diagnostic paradigm, mass spectroscopic serum proteomic pattern diagnostics was reported superior to the conventional serologic cancer biomarkers. Ho...
Henry Han
ICRA
1998
IEEE
148views Robotics» more  ICRA 1998»
13 years 11 months ago
Position Estimation Using Principal Components of Range Data
1 sensors is to construct a structural description from sensor data and to match this description to a previously acquired model [Crowley 85]. An alternative is to project individu...
James L. Crowley, Frank Wallner, Bernt Schiele