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PRL
2008
135views more  PRL 2008»
13 years 8 months ago
A hierarchical clustering algorithm based on the Hungarian method
We propose a novel hierarchical clustering algorithm for data-sets in which only pairwise distances between the points are provided. The classical Hungarian method is an efficient...
Jacob Goldberger, Tamir Tassa
ICDM
2008
IEEE
184views Data Mining» more  ICDM 2008»
14 years 3 months ago
Bayesian Co-clustering
In recent years, co-clustering has emerged as a powerful data mining tool that can analyze dyadic data connecting two entities. However, almost all existing co-clustering techniqu...
Hanhuai Shan, Arindam Banerjee
PR
2008
169views more  PR 2008»
13 years 8 months ago
A survey of kernel and spectral methods for clustering
Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with ...
Maurizio Filippone, Francesco Camastra, Francesco ...
ICDM
2009
IEEE
110views Data Mining» more  ICDM 2009»
14 years 3 months ago
Projective Clustering Ensembles
Recent advances in data clustering concern clustering ensembles and projective clustering methods, each addressing different issues in clustering problems. In this paper, we consi...
Francesco Gullo, Carlotta Domeniconi, Andrea Tagar...
COCOA
2008
Springer
13 years 10 months ago
New Algorithms for k-Center and Extensions
The problem of interest is covering a given point set with homothetic copies of several convex containers C1,...,Ck, while the objective is to minimize the maximum over the dilatat...
René Brandenberg, Lucia Roth