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ECSQARU
2005
Springer
16 years 9 days ago
Default Clustering from Sparse Data Sets
Categorization with a very high missing data rate is seldom studied, especially from a non-probabilistic point of view. This paper proposes a new algorithm called default clusterin...
Julien Velcin, Jean-Gabriel Ganascia
PAMI
1998
88views more  PAMI 1998»
15 years 6 months ago
Large-Scale Parallel Data Clustering
—Algorithmic enhancements are described that enable large computational reduction in mean square-error data clustering. These improvements are incorporated into a parallel data-c...
Dan Judd, Philip K. McKinley, Anil K. Jain
SDM
2004
SIAM
187views Data Mining» more  SDM 2004»
15 years 8 months ago
Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data
Microarray experiments have been extensively used for simultaneously measuring DNA expression levels of thousands of genes in genome research. A key step in the analysis of gene e...
Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvri...
JCB
2002
160views more  JCB 2002»
15 years 6 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
INFOVIS
1998
IEEE
15 years 11 months ago
Similarity Clustering of Dimensions for an Enhanced Visualization of Multidimensional Data
The order and arrangement of dimensions (variates) is crucial for the effectiveness of a large number of visualization techniques such as parallel coordinates, scatterplots, recur...
Mihael Ankerst, Stefan Berchtold, Daniel A. Keim