The eigenvalues of stochastic blockmodel graphs
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Abstract (arXiv)
We derive the limiting distribution for the largest eigenvalues of the adjacency matrix for a stochastic blockmodel graph when the number of vertices tends to infinity. We show that, in the limit, these eigenvalues are jointly multivariate normal with bounded covariances. Our result extends the classic result of F"uredi and Koml'os on the fluctuation of the largest eigenvalue for ErdHos-R'enyi graphs.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Mar 2018.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 1; 2024: 0; 2025: 1; 2026: 1.
7 papers.
- 2022Theoretical analysis and computation of the sample Frechet mean for sets of large graphs based on spectral informationcited by 2
- 2023Fast and Robust Sparsity-Aware Block Diagonal Representationcited by 1
- 2021Approximate Fr'echet Mean for Data Sets of Sparse Graphscited by 0
- 2022Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithmscited by 0
- 2022Probability density estimation for sets of large graphs with respect to spectral information using stochastic block modelscited by 0
- 2025The Spectral Barycentre of a Set of Graphs with Community Structurecited by 0
- 2026Random Dot Product Graphs as Dynamical Systems: Limitations and Opportunitiescited by 0
- 2026Random Dot Product Graphs as Dynamical Systems: Limitations and Opportunities5 Mar 2026
- 2025The Spectral Barycentre of a Set of Graphs with Community Structure26 Jan 2025
- 2023Fast and Robust Sparsity-Aware Block Diagonal Representation2 Dec 2023
- 2022Probability density estimation for sets of large graphs with respect to spectral information using stochastic block models5 Jul 2022
- 2022Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms8 Feb 2022
- 2022Theoretical analysis and computation of the sample Frechet mean for sets of large graphs based on spectral information15 Jan 2022
- 2021Approximate Fr'echet Mean for Data Sets of Sparse Graphs10 May 2021