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» Co-Scheduling of Computation and Data on Computer Clusters
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CIKM
2006
Springer
13 years 9 months ago
Efficiently clustering transactional data with weighted coverage density
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Hua Yan, Keke Chen, Ling Liu
ISVC
2009
Springer
14 years 1 months ago
Parallel 3D Image Segmentation of Large Data Sets on a GPU Cluster
In this paper, we propose an inherent parallel scheme for 3D image segmentation of large volume data on a GPU cluster. This method originates from an extended Lattice Boltzmann Mod...
Aaron Hagan, Ye Zhao
PDP
2003
IEEE
14 years 20 days ago
Scheduling strategies for mixed data and task parallelism on heterogeneous clusters and grids
We consider the execution of a complex application on a heterogeneous "grid" computing platform. The complex application consists of a suite of identical, independent pr...
Olivier Beaumont, Arnaud Legrand, Yves Robert
LKR
2008
13 years 8 months ago
Identification of MCMC Samples for Clustering
Abstract. For clustering problems, many studies use just MAP assignments to show clustering results instead of using whole samples from a MCMC sampler. This is because it is not st...
Kenichi Kurihara, Tsuyoshi Murata, Taisuke Sato
ICDM
2009
IEEE
175views Data Mining» more  ICDM 2009»
13 years 5 months ago
Maximum Margin Clustering with Multivariate Loss Function
This paper presents a simple but powerful extension of the maximum margin clustering (MMC) algorithm that optimizes multivariate performance measure specifically defined for clust...
Bin Zhao, James Tin-Yau Kwok, Changshui Zhang