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» Landscape of Clustering Algorithms
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ISPASS
2006
IEEE
15 years 10 months ago
Comparing multinomial and k-means clustering for SimPoint
SimPoint is a technique used to pick what parts of the program’s execution to simulate in order to have a complete picture of execution. SimPoint uses data clustering algorithms...
Greg Hamerly, Erez Perelman, Brad Calder
129
Voted
VTC
2006
IEEE
129views Communications» more  VTC 2006»
15 years 10 months ago
A Framework for Automatic Clustering of Parametric MIMO Channel Data Including Path Powers
— We present a solution to the problem of identifying clusters from MIMO measurement data in a data window, with a minimum of user interaction. Conventionally, visual inspection ...
Nicolai Czink, Pierluigi Cera, Jari Salo, Ernst Bo...
SSDBM
2005
IEEE
218views Database» more  SSDBM 2005»
15 years 10 months ago
The "Best K" for Entropy-based Categorical Data Clustering
With the growing demand on cluster analysis for categorical data, a handful of categorical clustering algorithms have been developed. Surprisingly, to our knowledge, none has sati...
Keke Chen, Ling Liu
COLT
2003
Springer
15 years 9 months ago
On Finding Large Conjunctive Clusters
We propose a new formulation of the clustering problem that differs from previous work in several aspects. First, the goal is to explicitly output a collection of simple and meani...
Nina Mishra, Dana Ron, Ram Swaminathan
SIGMOD
2000
ACM
165views Database» more  SIGMOD 2000»
15 years 9 months ago
Finding Generalized Projected Clusters In High Dimensional Spaces
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
Charu C. Aggarwal, Philip S. Yu