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» Topology for Distributed Inference on Graphs
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ICPR
2004
IEEE
16 years 4 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
118
Voted
IPPS
1999
IEEE
15 years 8 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...
139
Voted
CVPR
2003
IEEE
16 years 5 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
136
Voted
GLOBECOM
2007
IEEE
15 years 10 months 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
142
Voted
ECCV
2006
Springer
16 years 5 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