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ICPR
2004
IEEE
14 years 11 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
APPROX
2010
Springer
179views Algorithms» more  APPROX 2010»
13 years 12 months ago
Rumor Spreading on Random Regular Graphs and Expanders
Broadcasting algorithms are important building blocks of distributed systems. In this work we investigate the typical performance of the classical and well-studied push model. Assu...
Nikolaos Fountoulakis, Konstantinos Panagiotou
INFOCOM
2003
IEEE
14 years 3 months ago
Sampling Biases in IP Topology Measurements
— Considerable attention has been focused on the properties of graphs derived from Internet measurements. Router-level topologies collected via traceroute-like methods have led s...
Anukool Lakhina, John W. Byers, Mark Crovella, Pen...
ALENEX
2003
137views Algorithms» more  ALENEX 2003»
13 years 11 months ago
The Markov Chain Simulation Method for Generating Connected Power Law Random Graphs
Graph models for real-world complex networks such as the Internet, the WWW and biological networks are necessary for analytic and simulation-based studies of network protocols, al...
Christos Gkantsidis, Milena Mihail, Ellen W. Zegur...
ACL
2009
13 years 8 months ago
Markov Random Topic Fields
Most approaches to topic modeling assume an independence between documents that is frequently violated. We present an topic model that makes use of one or more user-specified grap...
Hal Daume III