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» Cluster computing for web-scale data processing
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PVLDB
2008
182views more  PVLDB 2008»
13 years 7 months ago
SCOPE: easy and efficient parallel processing of massive data sets
Companies providing cloud-scale services have an increasing need to store and analyze massive data sets such as search logs and click streams. For cost and performance reasons, pr...
Ronnie Chaiken, Bob Jenkins, Per-Åke Larson,...
IPMI
2009
Springer
14 years 8 months ago
Tractography Segmentation Using a Hierarchical Dirichlet Processes Mixture Model
In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. Th...
Carl-Fredrik Westin, W. Eric L. Grimson, Xiaogang ...
SDM
2009
SIAM
223views Data Mining» more  SDM 2009»
14 years 4 months ago
Context Aware Trace Clustering: Towards Improving Process Mining Results.
Process Mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms...
R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aa...
PDP
2010
IEEE
14 years 2 months ago
Experimental Study of Six Different Implementations of Parallel Matrix Multiplication on Heterogeneous Computational Clusters of
—Two strategies of distribution of computations can be used to implement parallel solvers for dense linear algebra problems for Heterogeneous Computational Clusters of Multicore ...
Pedro Alonso, Ravi Reddy, Alexey L. Lastovetsky
ICPR
2010
IEEE
13 years 11 months ago
CDP Mixture Models for Data Clustering
—In Dirichlet process (DP) mixture models, the number of components is implicitly determined by the sampling parameters of Dirichlet process. However, this kind of models usually...
Yangfeng Ji, Tong Lin, Hongbin Zha