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» On Generating Random Network Structures: Connected Graphs
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125
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IJWMC
2010
115views more  IJWMC 2010»
14 years 9 months ago
Small-world effects in wireless agent sensor networks
Coverage, fault tolerance and power consumption constraints make optimal placement of mobile sensors or other mobile agents a hard problem. We have developed a model for describin...
Kenneth A. Hawick, Heath A. James
102
Voted
SODA
2008
ACM
123views Algorithms» more  SODA 2008»
15 years 2 months ago
Delaunay graphs of point sets in the plane with respect to axis-parallel rectangles
Given a point set P in the plane, the Delaunay graph with respect to axis-parallel rectangles is a graph defined on the vertex set P, whose two points p, q P are connected by an ...
Xiaomin Chen, János Pach, Mario Szegedy, G&...
MSWIM
2004
ACM
15 years 6 months ago
Quantile models for the threshold range for k-connectivity
This study addresses the problem of k-connectivity of a wireless multihop network consisting of randomly placed nodes with a common transmission range, by utilizing empirical regr...
Henri Koskinen
115
Voted
IJAR
2010
152views more  IJAR 2010»
14 years 11 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
91
Voted
ICML
2010
IEEE
15 years 1 months ago
Learning Markov Logic Networks Using Structural Motifs
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
Stanley Kok, Pedro Domingos