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» Topology for Distributed Inference on Graphs
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ICPR
2004
IEEE
16 years 7 months ago
A Probabilistic Approach to Learning Costs for Graph Edit Distance
Graph edit distance provides an error-tolerant way to measure distances between attributed graphs. The effectiveness of edit distance based graph classification algorithms relies ...
Horst Bunke, Michel Neuhaus
IPPS
1999
IEEE
15 years 10 months ago
A new Architecture for Multihop Optical Networks
Multihop lightwave networks are becoming increasingly popular in optical networks. It is attractive to consider regular graphs as the logical topology for a multihop network, due t...
Arunita Jaekel, Subir Bandyopadhyay, Abhijit Sengu...
CVPR
2003
IEEE
16 years 8 months ago
PAMPAS: Real-Valued Graphical Models for Computer Vision
Probabilistic models have been adopted for many computer vision applications, however inference in highdimensional spaces remains problematic. As the statespace of a model grows, ...
Michael Isard
GLOBECOM
2007
IEEE
16 years 10 days ago
Colouring Link-Directional Interference Graphs in Wireless Ad Hoc Networks
—In this paper, we clarify inter-link interference in wireless ad-hoc networks by using link-directional interference graphs (l-graph). Most of the interference graphs in the lit...
Ping Chung Ng, David J. Edwards, Soung Chang Liew
ECCV
2006
Springer
16 years 8 months ago
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Daniel Cremers, Leo Grady