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» The Method of Quantum Clustering
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BMCBI
2010
151views more  BMCBI 2010»
15 years 1 months ago
Misty Mountain clustering: application to fast unsupervised flow cytometry gating
Background: There are many important clustering questions in computational biology for which no satisfactory method exists. Automated clustering algorithms, when applied to large,...
István P. Sugár, Stuart C. Sealfon
ICDM
2009
IEEE
110views Data Mining» more  ICDM 2009»
15 years 8 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...
INFORMATICALT
2008
124views more  INFORMATICALT 2008»
15 years 1 months ago
Hierarchical Adaptive Clustering
This paper studies an adaptive clustering problem. We focus on re-clustering an object set, previously clustered, when the feature set characterizing the objects increases. We prop...
Gabriela Serban, Alina Campan
PRL
2006
139views more  PRL 2006»
15 years 1 months ago
Adaptive Hausdorff distances and dynamic clustering of symbolic interval data
This paper presents a partitional dynamic clustering method for interval data based on adaptive Hausdorff distances. Dynamic clustering algorithms are iterative two-step relocatio...
Francisco de A. T. de Carvalho, Renata M. C. R. de...
COMPGEOM
2006
ACM
15 years 7 months ago
How slow is the k-means method?
The k-means method is an old but popular clustering algorithm known for its observed speed and its simplicity. Until recently, however, no meaningful theoretical bounds were known...
David Arthur, Sergei Vassilvitskii