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NIPS
2004
14 years 11 months ago
Maximum Margin Clustering
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...
NIPS
2003
14 years 11 months ago
Clustering with the Connectivity Kernel
Clustering aims at extracting hidden structure in dataset. While the problem of finding compact clusters has been widely studied in the literature, extracting arbitrarily formed ...
Bernd Fischer, Volker Roth, Joachim M. Buhmann
ICDM
2009
IEEE
171views Data Mining» more  ICDM 2009»
14 years 7 months ago
Hybrid Clustering by Integrating Text and Citation Based Graphs in Journal Database Analysis
We propose a hybrid clustering strategy by integrating heterogeneous information sources as graphs. The hybrid clustering method is extended on the basis of modularity based Louva...
Xinhai Liu, Shi Yu, Yves Moreau, Frizo A. L. Janss...
SDM
2009
SIAM
162views Data Mining» more  SDM 2009»
15 years 7 months ago
Diversity-Based Weighting Schemes for Clustering Ensembles.
Clustering ensembles has been recently recognized as an emerging approach to provide more robust solutions to the data clustering problem. Current methods of clustering ensembles ...
Andrea Tagarelli, Francesco Gullo, Sergio Greco
BMCBI
2008
144views more  BMCBI 2008»
14 years 10 months ago
WGCNA: an R package for weighted correlation network analysis
Background: Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method ...
Peter Langfelder, Steve Horvath