P. Bermolen, Valeria Goicoechea, M. Jonckheere, E. Mordecki
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Large Deviation Principle for the Greedy Exploration Algorithm over Erdös-Rényi Graphs
We prove a large deviation principle (LDP) for a greedy exploration process on an Erdos-Renyi (ER) graph when the number of nodes goes to this http URL prove our main result we use the general strategy for the study of large deviations of processes proposed by Feng and Kurtz (2006), which is based on the convergence of non-linear semigroups. The rate function can be expressed in a closed form formula and associated optimization problems can be solved explicitly providing the trajectory of the large deviation. In addition we derive a LDP for the size of the maximum independent set discovered by such algorithm and analyze the probability that it exceeds known bounds for the maximal independent set. We also analyze the link between these results and the landscape complexity of the independent set and the exploration dynamic.
期刊介绍:
ALEA publishes research articles in probability theory, stochastic processes, mathematical statistics, and their applications. It publishes also review articles of subjects which developed considerably in recent years. All articles submitted go through a rigorous refereeing process by peers and are published immediately after accepted.
ALEA is an electronic journal of the Latin-american probability and statistical community which provides open access to all of its content and uses only free programs. Authors are allowed to deposit their published article into their institutional repository, freely and with no embargo, as long as they acknowledge the source of the paper.
ALEA is affiliated with the Institute of Mathematical Statistics.