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» An overview of clustering methods
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FLAIRS
2004
13 years 10 months ago
Adaptive K-Means Clustering
Clustering is used to organize data for efficient retrieval. One of the problems in clustering is the identification of clusters in given data. A popular technique for clustering ...
Sanjiv K. Bhatia
CLASSIFICATION
2010
13 years 6 months ago
Intelligent Choice of the Number of Clusters in K-Means Clustering: An Experimental Study with Different Cluster Spreads
: The issue of determining "the right number of clusters" in K-Means has attracted considerable interest, especially in the recent years. Cluster intermix appears to be a...
Mark Ming-Tso Chiang, Boris Mirkin
CSB
2005
IEEE
115views Bioinformatics» more  CSB 2005»
14 years 2 months ago
A New Clustering Strategy with Stochastic Merging and Removing Based on Kernel Functions
With hierarchical clustering methods, divisions or fusions, once made, are irrevocable. As a result, when two elements in a bottom-up algorithm are assigned to one cluster, they c...
Huimin Geng, Hesham H. Ali
CAV
2009
Springer
105views Hardware» more  CAV 2009»
14 years 9 months ago
Transactional Memory: Glimmer of a Theory
Transactional memory (TM) is a promising paradigm for concurrent programming. This paper is an overview of our recent theoretical work on defining a theory of TM. We first recall s...
Rachid Guerraoui, Michal Kapalka
FMCO
2004
Springer
105views Formal Methods» more  FMCO 2004»
14 years 2 months ago
Program Generation and Components
Abstract. The first part of the paper gives a brief overview of metaprogramming, in particular program generation, and its use in software development. The second part introduces ...
Davide Ancona, Eugenio Moggi