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» Mining Concepts from Large SAGE Gene Expression Matrices
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KDD
2004
ACM
118views Data Mining» more  KDD 2004»
14 years 6 months ago
Parallel computation of high dimensional robust correlation and covariance matrices
The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices...
James Chilson, Raymond T. Ng, Alan Wagner, Ruben H...
IDA
2005
Springer
13 years 11 months ago
From Local Pattern Mining to Relevant Bi-cluster Characterization
Clustering or bi-clustering techniques have been proved quite useful in many application domains. A weakness of these techniques remains the poor support for grouping characterizat...
Ruggero G. Pensa, Jean-François Boulicaut
BMCBI
2008
124views more  BMCBI 2008»
13 years 6 months ago
Literature-aided meta-analysis of microarray data: a compendium study on muscle development and disease
Background: Comparative analysis of expression microarray studies is difficult due to the large influence of technical factors on experimental outcome. Still, the identified diffe...
Rob Jelier, Peter A. C. 't Hoen, Ellen Sterrenburg...

Publication
197views
12 years 1 months ago
Convex non-negative matrix factorization for massive datasets
Non-negative matrix factorization (NMF) has become a standard tool in data mining, information retrieval, and signal processing. It is used to factorize a non-negative data matrix ...
C. Thurau, K. Kersting, M. Wahabzada, and C. Bauck...