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CVPR
2003
IEEE
14 years 9 months ago
Robust Data Clustering
We address the problem of robust clustering by combining data partitions (forming a clustering ensemble) produced by multiple clusterings. We formulate robust clustering under an ...
Ana L. N. Fred, Anil K. Jain
JMLR
2002
73views more  JMLR 2002»
13 years 7 months ago
Variational Learning of Clusters of Undercomplete Nonsymmetric Independent Components
We apply a variational method to automatically determine the number of mixtures of independent components in high-dimensional datasets, in which the sources may be nonsymmetricall...
Kwokleung Chan, Te-Won Lee, Terrence J. Sejnowski
ICML
2008
IEEE
14 years 8 months ago
Statistical models for partial membership
We present a principled Bayesian framework for modeling partial memberships of data points to clusters. Unlike a standard mixture model which assumes that each data point belongs ...
Katherine A. Heller, Sinead Williamson, Zoubin Gha...
IWQOS
2004
Springer
14 years 1 months ago
Robust communications for sensor networks in hostile environments
— Clustering sensor nodes increases the scalability and energy efficiency of communications among them. In hostile environments, unexpected failures or attacks on cluster heads ...
Ossama Younis, Sonia Fahmy, Paolo Santi
PKDD
2009
Springer
175views Data Mining» more  PKDD 2009»
14 years 2 months ago
Latent Dirichlet Bayesian Co-Clustering
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...
Pu Wang, Carlotta Domeniconi, Kathryn B. Laskey