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ICML
2004
IEEE
16 years 7 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
COMPLIFE
2005
Springer
16 years 17 hour ago
Robust Perron Cluster Analysis for Various Applications in Computational Life Science
In the present paper we explain the basic ideas of Robust Perron Cluster Analysis (PCCA+) and exemplify the different application areas of this new and powerful method. Recently, ...
Marcus Weber, Susanna Kube
ECML
2005
Springer
15 years 8 months ago
Clustering and Metaclustering with Nonnegative Matrix Decompositions
Although very widely used in unsupervised data mining, most clustering methods are affected by the instability of the resulting clusters w.r.t. the initialization of the algorithm ...
Liviu Badea
ICPP
2009
IEEE
16 years 1 months ago
End-to-End Study of Parallel Volume Rendering on the IBM Blue Gene/P
—In addition to their role as simulation engines, modern supercomputers can be harnessed for scientific visualization. Their extensive concurrency, parallel storage systems, and...
Tom Peterka, Hongfeng Yu, Robert B. Ross, Kwan-Liu...
PRIB
2009
Springer
147views Bioinformatics» more  PRIB 2009»
16 years 1 months ago
Cross-Platform Analysis with Binarized Gene Expression Data
Abstract. With widespread use of microarray technology as a potential diagnostics tool, the comparison of results obtained from the use of different platforms is of interest. When...
Salih Tuna, Mahesan Niranjan