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» Generating Random Graphs with Large Girth
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CN
2010
121views more  CN 2010»
13 years 7 months ago
Probabilistic flooding for efficient information dissemination in random graph topologies
Probabilistic flooding has been frequently considered as a suitable dissemination information approach for limiting the large message overhead associated with traditional (full) f...
Konstantinos Oikonomou, Dimitrios Kogias, Ioannis ...
MICS
2010
134views more  MICS 2010»
13 years 9 months ago
Scale Free Properties of Random k-Trees
Scale free graphs have attracted attention as their non-uniform structure that can be used as a model for many social networks including the WWW and the Internet. In this paper, w...
Colin Cooper, Ryuhei Uehara
ICML
2004
IEEE
14 years 11 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
VALUETOOLS
2006
ACM
176views Hardware» more  VALUETOOLS 2006»
14 years 4 months ago
How to solve large scale deterministic games with mean payoff by policy iteration
Min-max functions are dynamic programming operators of zero-sum deterministic games with finite state and action spaces. The problem of computing the linear growth rate of the or...
Vishesh Dhingra, Stephane Gaubert
ICS
2010
Tsinghua U.
14 years 8 months ago
Local Algorithms for Finding Interesting Individuals in Large Networks
: We initiate the study of local, sublinear time algorithms for finding vertices with extreme topological properties -- such as high degree or clustering coefficient -- in large so...
Mickey Brautbar, Michael Kearns