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cs.SI2026
Spectral graph clustering with inhomogeneous latent geometry
Konstantin Avrachenkov, Lucas S. Sibemberg, Alexander Van Werde
We study spectral clustering in the presence of a confounding latent geometry. The leading eigenvectors may then be dominated by the latent geometry rather than by the communities.…
cs.SI2025
Multi-Community Spectral Clustering for Geometric Graphs
Luiz Emilio Allem, Konstantin Avrachenkov, Carlos Hoppen +2
In this paper, we consider the soft geometric block model (SGBM) with a fixed number of homogeneous communities in the dense regime, and we introduce a spectral clusteri…
cs.SI2020
A spectral clustering approach for the evolution of the COVID-19 pandemic in the state of Rio Grande do Sul, Brazil
Luiz Emilio Allem, Carlos Hoppen, Matheus Micadei Marzo +1
The aim of this paper is to analyse the evolution of the COVID-19 pandemic in Rio Grande do Sul by applying graph-theoretical tools, particularly spectral clustering techniques, on…