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» Hartigan's Method: k-means Clustering without Voronoi
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JMLR
2010
225views more  JMLR 2010»
13 years 2 months ago
Hartigan's Method: k-means Clustering without Voronoi
Hartigan's method for k-means clustering is the following greedy heuristic: select a point, and optimally reassign it. This paper develops two other formulations of the heuri...
Matus Telgarsky, Andrea Vattani
ICML
2007
IEEE
14 years 8 months ago
Best of both: a hybridized centroid-medoid clustering heuristic
Although each iteration of the popular kMeans clustering heuristic scales well to larger problem sizes, it often requires an unacceptably-high number of iterations to converge to ...
Nizar Grira, Michael E. Houle
WWW
2010
ACM
13 years 11 months ago
Hierarchical cluster visualization in web mapping systems
This paper presents a technique for visualizing large spatial data sets in Web Mapping Systems (WMS). The technique creates a hierarchical clustering tree, which is subsequently u...
Jean-Yves Delort
ESWA
2008
213views more  ESWA 2008»
13 years 7 months ago
Visualization of patent analysis for emerging technology
Many methods have been developed to recognize those progresses of technologies, and one of them is to analyze patent information. And visualization methods are considered to be pr...
Young Gil Kim, Jong Hwan Suh, Sang-Chan Park
MICCAI
2009
Springer
14 years 8 months ago
Tractography-Based Parcellation of the Cortex Using a Spatially-Informed Dimension Reduction of the Connectivity Matrix
Determining cortical functional areas is an important goal for neurosciences and clinical neurosurgery. This paper presents a method for connectivity-based parcellation of the enti...
Cyril Poupon, Denis Rivière, Jean-Francois ...