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» An overview of clustering methods
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NIPS
2003
13 years 10 months ago
Geometric Clustering Using the Information Bottleneck Method
We argue that K–means and deterministic annealing algorithms for geometric clustering can be derived from the more general Information Bottleneck approach. If we cluster the ide...
Susanne Still, William Bialek, Léon Bottou
CVIU
1999
238views more  CVIU 1999»
13 years 8 months ago
A Coarse to Fine 3D Registration Method Based on Robust Fuzzy Clustering
An important problem in computer vision is to determine how features extracted from images are connected to an existing model. In this paper, we focus on solving the registration ...
Jean-Philippe Tarel, Nozha Boujemaa
PR
2010
156views more  PR 2010»
13 years 7 months ago
The hyperbolic smoothing clustering method
It is considered the minimum sum-of-squares clustering problem. The mathematical modeling of this problem leads to a min − sum − min formulation which, in addition to its intr...
Adilson Elias Xavier
ICCD
2007
IEEE
157views Hardware» more  ICCD 2007»
14 years 5 months ago
Combining cluster sampling with single pass methods for efficient sampling regimen design
Microarchitectural simulation is orders of magnitude slower than native execution. As more elements are accurately modeled, problems associated with slow simulation are further ex...
Paul D. Bryan, Thomas M. Conte
ESEM
2007
ACM
13 years 10 months ago
An Approach to Outlier Detection of Software Measurement Data using the K-means Clustering Method
The quality of software measurement data affects the accuracy of project manager’s decision making using estimation or prediction models and the understanding of real project st...
Kyung-A Yoon, Oh-Sung Kwon, Doo-Hwan Bae