A Note on the Identifiability of the Degree-Corrected Stochastic Block Model

Fuente: arXiv
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Autores principales: Park, John, Zhao, Yunpeng, Hao, Ning
Formato: Preprint
Publicado: 2024
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author Park, John
Zhao, Yunpeng
Hao, Ning
author_facet Park, John
Zhao, Yunpeng
Hao, Ning
contents In this short note, we address the identifiability issues inherent in the Degree-Corrected Stochastic Block Model (DCSBM). We provide a rigorous proof demonstrating that the parameters of the DCSBM are identifiable up to a scaling factor and a permutation of the community labels, under a mild condition.
format Preprint
id arxiv_https___arxiv_org_abs_2412_03833
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Note on the Identifiability of the Degree-Corrected Stochastic Block Model
Park, John
Zhao, Yunpeng
Hao, Ning
Methodology
In this short note, we address the identifiability issues inherent in the Degree-Corrected Stochastic Block Model (DCSBM). We provide a rigorous proof demonstrating that the parameters of the DCSBM are identifiable up to a scaling factor and a permutation of the community labels, under a mild condition.
title A Note on the Identifiability of the Degree-Corrected Stochastic Block Model
topic Methodology
url https://arxiv.org/abs/2412.03833