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ICCAD
2000
IEEE
104views Hardware» more  ICCAD 2000»
15 years 11 months ago
Diagnosis of Interconnect Faults in Cluster-Based FPGA Architectures
— Fault diagnosis has particular importance in the context of field programmable gate arrays (FPGAs) because faults can be avoided by reconfiguration at almost no real cost. Cl...
Ian G. Harris, Russell Tessier
EUROPAR
1999
Springer
15 years 10 months ago
Parallel k/h-Means Clustering for Large Data Sets
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
Kilian Stoffel, Abdelkader Belkoniene
IJCAI
1989
15 years 7 months ago
Concept Formation by Incremental Conceptual Clustering
Incremental conceptual clustering is an important area of machine learning. It is concerned with summarizing data in a form of concept hierarchies, which will eventually ease the ...
Mirsad Hadzikadic, David Y. Y. Yun
PRL
2007
150views more  PRL 2007»
15 years 6 months ago
A method for initialising the K-means clustering algorithm using kd-trees
We present a method for initialising the K-means clustering algorithm. Our method hinges on the use of a kd-tree to perform a density estimation of the data at various locations. ...
Stephen J. Redmond, Conor Heneghan
JMLR
2010
225views more  JMLR 2010»
15 years 1 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