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» Stability of k -Means Clustering
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BMCBI
2010
139views more  BMCBI 2010»
13 years 8 months ago
A highly efficient multi-core algorithm for clustering extremely large datasets
Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
Johann M. Kraus, Hans A. Kestler
BMCBI
2004
208views more  BMCBI 2004»
13 years 8 months ago
Hybrid clustering for microarray image analysis combining intensity and shape features
Background: Image analysis is the first crucial step to obtain reliable results from microarray experiments. First, areas in the image belonging to single spots have to be identif...
Jörg Rahnenführer, Daniel Bozinov
SIGMETRICS
2002
ACM
104views Hardware» more  SIGMETRICS 2002»
13 years 7 months ago
Improving cluster availability using workstation validation
We demonstrate a framework for improving the availability of cluster based Internet services. Our approach models Internet services as a collection of interconnected components, e...
Taliver Heath, Richard P. Martin, Thu D. Nguyen
COMPGEOM
2006
ACM
14 years 2 months ago
A fast k-means implementation using coresets
In this paper we develop an efficient implementation for a k-means clustering algorithm. The novel feature of our algorithm is that it uses coresets to speed up the algorithm. A ...
Gereon Frahling, Christian Sohler
EDBT
2006
ACM
191views Database» more  EDBT 2006»
14 years 8 months ago
Distributed Spatial Clustering in Sensor Networks
Abstract. Sensor networks monitor physical phenomena over large geographic regions. Scientists can gain valuable insight into these phenomena, if they understand the underlying dat...
Anand Meka, Ambuj K. Singh