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PRIS
2004
13 years 10 months ago
Comparison of Combination Methods using Spectral Clustering Ensembles
We address the problem of the combination of multiple data partitions, that we call a clustering ensemble. We use a recent clustering approach, known as Spectral Clustering, and th...
André Lourenço, Ana L. N. Fred
BMCBI
2007
130views more  BMCBI 2007»
13 years 8 months ago
A robust measure of correlation between two genes on a microarray
Background: The underlying goal of microarray experiments is to identify gene expression patterns across different experimental conditions. Genes that are contained in a particula...
Johanna S. Hardin, Aya Mitani, Leanne Hicks, Brian...
KDD
2008
ACM
119views Data Mining» more  KDD 2008»
14 years 9 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
CLOUD
2010
ACM
14 years 1 months ago
Robust and flexible power-proportional storage
Power-proportional cluster-based storage is an important component of an overall cloud computing infrastructure. With it, substantial subsets of nodes in the storage cluster can b...
Hrishikesh Amur, James Cipar, Varun Gupta, Gregory...
CIS
2008
Springer
13 years 10 months ago
Cooperation Controlled Competitive Learning Approach for Data Clustering
Rival Penalized Competitive Learning (RPCL) and its variants can perform clustering analysis efficiently with the ability of selecting the cluster number automatically. Although t...
Tao Li, Wenjiang Pei, Shao-ping Wang, Yiu-ming Che...