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Correlated randomly growing graphs

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If you have a question about this talk, please contact Dr Sergio Bacallado.

Correlated random graph models have received much attention recently due to their relevance to various applications, for instance understanding the graph matching problem in an average-case setting. In this talk I will discuss models of correlated randomly growing graphs. I will focus on the fundamental statistical questions of detecting correlation and estimating aspects of the correlated structure. Our results highlight the influence of the seed graph in the underlying growth model and its connections with these detection and estimation questions. This is based on joint work with Anirudh Sridhar.

This talk is part of the Statistics series.

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