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» Principal Component Analysis Based on L1-Norm Maximization
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BMCBI
2008
121views more  BMCBI 2008»
13 years 9 months ago
Stability of gene contributions and identification of outliers in multivariate analysis of microarray data
Background: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages com...
Florent Baty, Daniel Jaeger, Frank Preiswerk, Mart...
BMCBI
2006
102views more  BMCBI 2006»
13 years 8 months ago
Microarray analysis distinguishes differential gene expression patterns from large and small colony Thymidine kinase mutants of
Background: The Thymidine kinase (Tk) mutants generated from the widely used L5178Y mouse lymphoma assay fall into two categories, small colony and large colony. Cells from the la...
Tao Han, Jianyong Wang, Weida Tong, Martha M. Moor...
TIP
2008
128views more  TIP 2008»
13 years 8 months ago
The Pairing of a Wavelet Basis With a Mildly Redundant Analysis via Subband Regression
A distinction is usually made between wavelet bases and wavelet frames. The former are associated with a one-to-one representation of signals, which is somewhat constrained but mos...
Michael Unser, Dimitri Van De Ville
DEBU
2008
186views more  DEBU 2008»
13 years 8 months ago
A Survey of Collaborative Recommendation and the Robustness of Model-Based Algorithms
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...
Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke
ICNC
2005
Springer
14 years 2 months ago
Line-Based PCA and LDA Approaches for Face Recognition
Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) techniques are important and well-developed area of image recognition and to date many linear discriminati...
Vo Dinh Minh Nhat, Sungyoung Lee