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» Approximate Discovery of Random Graphs
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CVPR
2004
IEEE
14 years 9 months ago
Graphical Models for Graph Matching
This paper explores a formulation for attributed graph matching as an inference problem over a hidden Markov Random Field. We approximate the fully connected model with simpler mo...
Dante Augusto Couto Barone, Terry Caelli, Tib&eacu...
JCT
2007
117views more  JCT 2007»
13 years 7 months ago
Large independent sets in regular graphs of large girth
Let G be a d-regular graph with girth g, and let α be the independence number of G. We show that α(G) ≥ 1 2 1 − (d − 1)−2/(d−2) − (g) n where (g) → 0 as g → ∞,...
Joseph Lauer, Nicholas C. Wormald
FUIN
2006
139views more  FUIN 2006»
13 years 7 months ago
Efficient Parallel Query Processing by Graph Ranking
In this paper we deal with the problem of finding an optimal query execution plan in database systems. We improve the analysis of a polynomial-time approximation algorithm due to M...
Dariusz Dereniowski, Marek Kubale
TSP
2008
151views more  TSP 2008»
13 years 7 months ago
Convergence Analysis of Reweighted Sum-Product Algorithms
Markov random fields are designed to represent structured dependencies among large collections of random variables, and are well-suited to capture the structure of real-world sign...
Tanya Roosta, Martin J. Wainwright, Shankar S. Sas...
INFOCOM
2005
IEEE
14 years 1 months ago
BARD: Bayesian-assisted resource discovery in sensor networks
Data dissemination in sensor networks requires four components: resource discovery, route establishment, packet forwarding, and route maintenance. Resource discovery can be the mos...
Fred Stann, John S. Heidemann