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» Robust Parameterized Component Analysis
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BMCBI
2008
95views more  BMCBI 2008»
13 years 7 months ago
Unsupervised reduction of random noise in complex data by a row-specific, sorted principal component-guided method
Background: Large biological data sets, such as expression profiles, benefit from reduction of random noise. Principal component (PC) analysis has been used for this purpose, but ...
Joseph W. Foley, Fumiaki Katagiri
ICIP
2002
IEEE
14 years 9 months ago
A kernel machine based approach for multi-view face recognition
Techniques that can introduce low-dimensional feature representation with enhanced discriminatory power is of paramount importance in face recognition applications. It is well kno...
Juwei Lu, Kostas N. Plataniotis, Anastasios N. Ven...
CLUSTER
2009
IEEE
14 years 12 days ago
Numerically stable, single-pass, parallel statistics algorithms
—Statistical analysis is widely used for countless scientific applications in order to analyze and infer meaning from data. A key challenge of any statistical analysis package a...
Janine Bennett, R. Grout, Philippe P. Pébay...
ICA
2004
Springer
14 years 1 months ago
Second-Order Blind Source Separation Based on Multi-dimensional Autocovariances
SOBI is a blind source separation algorithm based on time decorrelation. It uses multiple time autocovariance matrices, and performs joint diagonalization thus being more robust th...
Fabian J. Theis, Anke Meyer-Bäse, Elmar Wolfg...
BMCBI
2010
161views more  BMCBI 2010»
13 years 7 months ago
BPDA - A Bayesian peptide detection algorithm for mass spectrometry
Background: Mass spectrometry (MS) is an essential analytical tool in proteomics. Many existing algorithms for peptide detection are based on isotope template matching and usually...
Youting Sun, Jianqiu Zhang, Ulisses Braga-Neto, Ed...