On the Minimax Misclassification Ratio of Hypergraph Community Detection

Community detection in hypergraphs is explored. Under a generative hypergraph model called " d -wise hypergraph stochastic block model" ( d - \mathtt {hSBM} ), which naturally extends the stochastic block model ( \mathtt {SBM} ) from graphs to d -uniform hypergraphs, the fundamental limit...

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Veröffentlicht in:	IEEE transactions on information theory 2019-12, Vol.65 (12), p.8095-8118
Hauptverfasser:	Chien, I Eli, Lin, Chung-Yi, Wang, I-Hsiang
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Asymptotic properties asymptotic theory Bayes methods Clustering Clustering algorithms Community detection Community relations Computational modeling Consistency Decay rate Divergence Graph theory Graphs hypergraph clustering hypergraph Laplacian Image edge detection Lower bounds Maximum likelihood estimation Minimax technique Parameter estimation Polynomials Probabilistic logic Probabilistic models Probability theory Risk Statistical analysis stochastic block model (SBM) Stochastic processes two-step algorithm Upper bounds
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