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NIPS
2003
14 years 11 months ago
An Iterative Improvement Procedure for Hierarchical Clustering
We describe a procedure which finds a hierarchical clustering by hillclimbing. The cost function we use is a hierarchical extension of the  -means cost; our local moves are tree...
David Kauchak, Sanjoy Dasgupta
84
Voted
PAKDD
2009
ACM
123views Data Mining» more  PAKDD 2009»
15 years 2 months ago
Clustering with Lower Bound on Similarity
We propose a new method, called SimClus, for clustering with lower bound on similarity. Instead of accepting k the number of clusters to find, the alternative similarity-based app...
Mohammad Al Hasan, Saeed Salem, Benjarath Pupacdi,...
BC
2005
77views more  BC 2005»
14 years 10 months ago
Motion repulsion arises from stimulus statistics when analyzed with a clustering algorithm
Motion repulsion is the perceived enlargement of the angle between the directions of motion of two transparently moving patterns. An explanation of this illusion has long been soug...
Alireza S. Mahani, Anders E. Carlsson, Ralf Wessel
CGO
2006
IEEE
15 years 4 months ago
Compiler-directed Data Partitioning for Multicluster Processors
Multicluster architectures overcome the scaling problem of centralized resources by distributing the datapath, register file, and memory subsystem across multiple clusters connec...
Michael L. Chu, Scott A. Mahlke
CIDM
2009
IEEE
15 years 4 months ago
Density-based clustering of polygons
– Clustering is an important task in spatial data mining and spatial analysis. We propose a clustering algorithm P-DBSCAN to cluster polygons in space. PDBSCAN is based on the we...
Deepti Joshi, Ashok Samal, Leen-Kiat Soh