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Approximate Fréchet Mean for Data Sets of Sparse Graphs

10 May 2021
Daniel Ferguson
Franccois G. Meyer
ArXiv (abs)PDFHTML
Abstract

To characterize the location (mean, median) of a set of graphs, one needs a notion of centrality that is adapted to metric spaces, since graph sets are not Euclidean spaces. A standard approach is to consider the Fr\échet mean. In this work, we equip a set of graph with the pseudometric defined by the ℓ2\ell_2ℓ2​ norm between the eigenvalues of their respective adjacency matrix . Unlike the edit distance, this pseudometric reveals structural changes at multiple scales, and is well adapted to studying various statistical problems on sets of graphs. We describe an algorithm to compute an approximation to the Fr\échet mean of a set of undirected unweighted graphs with a fixed size.

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