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Entropy 2016, 18(2), 53; doi:10.3390/e18020053

Bounding Extremal Degrees of Edge-Independent Random Graphs Using Relative Entropy

Department of Mathematics, Tongji University, Shanghai 200092, China
Academic Editor: J. A. Tenreiro Machado
Received: 2 December 2015 / Revised: 1 February 2016 / Accepted: 1 February 2016 / Published: 5 February 2016
(This article belongs to the Section Complexity)
View Full-Text   |   Download PDF [256 KB, uploaded 5 February 2016]   |  


Edge-independent random graphs are a model of random graphs in which each potential edge appears independently with an individual probability. Based on the relative entropy method, we determine the upper and lower bounds for the extremal vertex degrees using the edge probability matrix and its largest eigenvalue. Moreover, an application to random graphs with given expected degree sequences is presented. View Full-Text
Keywords: extremal degree; relative entropy; edge-independent random graph extremal degree; relative entropy; edge-independent random graph

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Shang, Y. Bounding Extremal Degrees of Edge-Independent Random Graphs Using Relative Entropy. Entropy 2016, 18, 53.

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