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1,544
A fast and flexible statistical model for largescale population genotype data: Applications to inferring missing genotypes and haplotype phase
 American Journal of Human Genetics
, 2005
"... We present a statistical model for patterns of genetic variation in samples of unrelated individuals from natural populations. This model is based on the idea that, over short regions, haplotypes in a population tend to cluster into groups of similar haplotypes. To capture the fact that, because of ..."
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Cited by 408 (10 self)
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We present a statistical model for patterns of genetic variation in samples of unrelated individuals from natural populations. This model is based on the idea that, over short regions, haplotypes in a population tend to cluster into groups of similar haplotypes. To capture the fact that, because
Creating efficient codebooks for visual recognition
 In Proceedings of the IEEE International Conference on Computer Vision
, 2005
"... Visual codebook based quantization of robust appearance descriptors extracted from local image patches is an effective means of capturing image statistics for texture analysis and scene classification. Codebooks are usually constructed by using a method such as kmeans to cluster the descriptor vect ..."
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Cited by 276 (22 self)
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statistics. We show that for dense sampling, kmeans overadapts to this, clustering centres almost exclusively around the densest few regions in descriptor space and thus failing to code other informative regions. This gives suboptimal codes that are no better than using randomly selected centres. We
Genetic algorithmbased clustering technique
 Pattern Recognition
, 2000
"... A genetic algorithmbased clustering technique, called GAclustering, is proposed in this article. The searching capability of genetic algorithms is exploited in order to search for appropriate cluster centres in the feature space such that a similarity metric of the resulting clusters is optimized. ..."
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Cited by 86 (0 self)
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A genetic algorithmbased clustering technique, called GAclustering, is proposed in this article. The searching capability of genetic algorithms is exploited in order to search for appropriate cluster centres in the feature space such that a similarity metric of the resulting clusters is optimized
KMeans Clustering
, 2006
"... The Kmeans algorithm (Bishop, 1995) is an algorithm for identifying K groups/clusters of data points in multidimensional spaces. Suppose we have a set of N data points {x1,..., xN} where xi ∈ RD, the basic goal is to find K groupings of the data points such that the intracluster distances of the p ..."
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of the points from their respective cluster centre, µi, is small. Formally, the objective is to recover the K class assignments that minimize the total intracluster squared Euclidean distance of each point to its cluster centre, µi: N ∑ K∑ J = on,i‖xn − µi ‖ 2, (1) n=1 i=1 where on,i is a binary variable
Clustering search algorithm for the capacitated centred clustering problem
 Computers & Operations Research
, 2010
"... The Capacitated Centred Clustering Problem (CCCP) consists in partitioning a set of n points into p disjoint clusters with a known capacity. Each cluster is specified by a centroid. The objective is to minimize the total dissimilarity within each cluster, such that a given capacity limit of the clus ..."
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Cited by 4 (0 self)
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The Capacitated Centred Clustering Problem (CCCP) consists in partitioning a set of n points into p disjoint clusters with a known capacity. Each cluster is specified by a centroid. The objective is to minimize the total dissimilarity within each cluster, such that a given capacity limit
On the dissolution of star clusters in the Galactic Centre
 I. Circular
, 2009
"... We present Nbody simulations of dissolving star clusters close to Galactic Centres. For this purpose, we developed a new Nbody program called NBODY6GC based on Aarseth’s series of Nbody codes. We describe the algorithm in detail. We report about the density wave phenomenon in the tidal arms which ..."
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Cited by 1 (0 self)
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We present Nbody simulations of dissolving star clusters close to Galactic Centres. For this purpose, we developed a new Nbody program called NBODY6GC based on Aarseth’s series of Nbody codes. We describe the algorithm in detail. We report about the density wave phenomenon in the tidal arms
Cluster Evolution at the Genome Sciences Centre
"... High Performance Computing has become a leading technology in the field of Bioinformatics. This is partly due to the completion of the Human Genome Project and many various other genome projects around the globe. These projects generated a lot of genetic data, which when mined, could improve our und ..."
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understanding of the many mysteries of biology and diseases like cancer. OSCAR has helped us demystify cluster deployment and management and its collection of leading clustering technologies has greatly enhanced our ability to harness our resource to generate and analyze data at an efficient rate. This paper
Interactions of Radio Galaxies and the IntraCluster Medium in
, 2008
"... Wide angle tailed radio galaxies (WATs) are objects located at or near cluster centres, with long plumes that are often bent, and are generally hosted by the dominant cluster galaxy. However, not all radio galaxies with bent plumes meet our definition of a WAT. We ..."
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Wide angle tailed radio galaxies (WATs) are objects located at or near cluster centres, with long plumes that are often bent, and are generally hosted by the dominant cluster galaxy. However, not all radio galaxies with bent plumes meet our definition of a WAT. We
Results 1  10
of
1,544