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» Anti-Ramsey properties of random graphs
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PODC
2006
ACM
14 years 2 months ago
Computing separable functions via gossip
Motivated by applications to sensor, peer-to-peer, and adhoc networks, we study the problem of computing functions of values at the nodes in a network in a totally distributed man...
Damon Mosk-Aoyama, Devavrat Shah
CORR
2006
Springer
102views Education» more  CORR 2006»
13 years 8 months ago
Structural Inference of Hierarchies in Networks
One property of networks that has received comparatively little attention is hierarchy, i.e., the property of having vertices that cluster together in groups, which then join to f...
Aaron Clauset, Cristopher Moore, M. E. J. Newman
TSP
2008
151views more  TSP 2008»
13 years 8 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...
JSAT
2006
73views more  JSAT 2006»
13 years 8 months ago
Impurity: Another Phase Transition of SAT
It is well known that satisfiability of random sets of propositional clauses undergoes phase transition while the clause-to-variable ratio of the sets increases. We introduce anot...
Eliezer L. Lozinskii
ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
13 years 6 months ago
Clustering Large Attributed Graphs: An Efficient Incremental Approach
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
Yang Zhou, Hong Cheng, Jeffrey Xu Yu