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Exact Recovery in the General Hypergraph Stochastic Block Model. (arXiv:2105.04770v2 [cs.IT] UPDATED)
Sept. 12, 2022, 1:12 a.m. | Qiaosheng Zhang, Vincent Y. F. Tan
stat.ML updates on arXiv.org arxiv.org
This paper investigates fundamental limits of exact recovery in the general
d-uniform hypergraph stochastic block model (d-HSBM), wherein n nodes are
partitioned into k disjoint communities with relative sizes (p1,..., pk). Each
subset of nodes with cardinality d is generated independently as an order-d
hyperedge with a certain probability that depends on the ground-truth
communities that the d nodes belong to. The goal is to exactly recover the k
hidden communities based on the observed hypergraph. We show that there …
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