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» An overview of clustering methods
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FLAIRS
2004
15 years 7 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
15 years 3 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»
15 years 11 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»
16 years 6 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»
15 years 11 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