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» A Framework for Visualising Large Graphs
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WIOPT
2010
IEEE
14 years 10 months ago
K-shell decomposition for dynamic complex networks
—K-shell (or k-core) graph decomposition methods were introduced as a tool for studying the structure of large graphs. K-shell decomposition methods have been recently proposed [...
Daniele Miorandi, Francesco De Pellegrini
IROS
2007
IEEE
125views Robotics» more  IROS 2007»
15 years 6 months ago
Hybrid localization using the hierarchical atlas
— This paper presents a hybrid localization scheme for a mobile robot using the hierarchical atlas. The hierarchical atlas is a map that consists of a higher level topological gr...
Stephen Tully, Hyungpil Moon, Deryck Morales, Geor...
ICVGIP
2004
15 years 1 months ago
Improved Cut-Based Foreground Identification
Automatic content based schemes, as opposed to those with human endeavor, have become important as users attempt to organize massive data presented in the form of multimedia data ...
Sharat Chandran, Satwik Hebbar, Vishal Mamania, Ab...
SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 2 months ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
UAI
2004
15 years 1 months ago
Convolutional Factor Graphs as Probabilistic Models
Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. ...
Yongyi Mao, Frank R. Kschischang, Brendan J. Frey