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» Using Library Dependencies for Clustering
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AI
2006
Springer
13 years 8 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth
CLUSTER
2006
IEEE
13 years 11 months ago
Lightweight I/O for Scientific Applications
Today's high-end massively parallel processing (MPP) machines have thousands to tens of thousands of processors, with next-generation systems planned to have in excess of one...
Ron Oldfield, Lee Ward, Rolf Riesen, Arthur B. Mac...
EUROPAR
2008
Springer
13 years 9 months ago
Reducing Kernel Development Complexity in Distributed Environments
Setting up generic and fully transparent distributed services for clusters implies complex and tedious kernel developments. More flexible approaches such as user-space libraries ar...
Adrien Lebre, Renaud Lottiaux, Erich Focht, Christ...
ICPR
2006
IEEE
14 years 9 months ago
Learning Wormholes for Sparsely Labelled Clustering
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
Eng-Jon Ong, Richard Bowden
ICMCS
2006
IEEE
150views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Hierarchical Summarization of Videos by Tree-Structured Vector Quantization
Accurate grouping of video shots could lead to semantic indexing of video segments for content analysis and retrieval. This paper introduces a novel cluster analysis which, depend...
Sergio Benini, Aldo Bianchetti, Riccardo Leonardi,...