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» Fully distributed EM for very large datasets
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ICML
2008
IEEE
14 years 5 months ago
Fully distributed EM for very large datasets
In EM and related algorithms, E-step computations distribute easily, because data items are independent given parameters. For very large data sets, however, even storing all of th...
Jason Wolfe, Aria Haghighi, Dan Klein
VLDB
2004
ACM
119views Database» more  VLDB 2004»
14 years 4 months ago
Evaluating holistic aggregators efficiently for very large datasets
Indatawarehousingapplications,numerousOLAP queries involve the processing of holistic aggregators such as computing the "top n," median, quantiles, etc. In this paper, we...
Lixin Fu, Sanguthevar Rajasekaran
SEMWEB
2010
Springer
13 years 2 months ago
Optimize First, Buy Later: Analyzing Metrics to Ramp-Up Very Large Knowledge Bases
As knowledge bases move into the landscape of larger ontologies and have terabytes of related data, we must work on optimizing the performance of our tools. We are easily tempted t...
Paea LePendu, Natalya Fridman Noy, Clement Jonquet...
MMM
2005
Springer
185views Multimedia» more  MMM 2005»
13 years 10 months ago
Database Support for Haptic Exploration in Very Large Virtual Environments
The efficient management of complex objects has become an enabling technology for modern multimedia information systems as well as for many novel database applications. Unfortunat...
Hans-Peter Kriegel, Peter Kunath, Martin Pfeifle, ...
BILDMED
2009
124views Algorithms» more  BILDMED 2009»
13 years 5 months ago
Evaluation of the Twofold Gaussian Mixture Model Applied to Clinical Volume Datasets
Abstract. Volume representations of blood vessels acquired by 3D rotational angiography are very suitable for diagnosing a stenosis or an aneurysm. For optimal treatment, physician...
Jan Bruijns