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Clustered Graph Matching for Label Recovery and Graph Classification
Given a collection of vertex-aligned networks and an additional label-shuffled network, we propose procedures for leveraging the signal in the vertex-aligned collection to recover the labels of the shuffled network.
The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference across Multiple Networks
We describe how this omnibus embedding can itself induce correlation, leading us to distinguish between inherent correlation -- the correlation that arises naturally in multisample network data -- and induced correlation, which is an artifice of the joint embedding methodology.
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