Sparse and smooth: improved guarantees for spectral clustering in the dynamic stochastic block model
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Publication:2136643
DOI10.1214/22-EJS1986MaRDI QIDQ2136643
Samuel Vaiter, Nicolas Keriven
Publication date: 11 May 2022
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2002.02892
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Cites Work
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- Kernel spectral clustering of large dimensional data
- Sharp nonasymptotic bounds on the norm of random matrices with independent entries
- Detecting communities and their evolutions in dynamic social networks -- a Bayesian approach
- Spectral clustering and the high-dimensional stochastic blockmodel
- Spectral clustering in the dynamic stochastic block model
- A variational approach to the consistency of spectral clustering
- A proof of the block model threshold conjecture
- Limit theorems for eigenvectors of the normalized Laplacian for random graphs
- Consistency of maximum-likelihood and variational estimators in the stochastic block model
- Consistency of the maximum likelihood and variational estimators in a dynamic stochastic block model
- Spectral and matrix factorization methods for consistent community detection in multi-layer networks
- Consistency of spectral clustering in stochastic block models
- Role of normalization in spectral clustering for stochastic blockmodels
- Consistency of spectral clustering
- Spectral redemption in clustering sparse networks
- Continuous Empirical Characteristic Function Estimation of Mixtures of Normal Parameters
- Approximating Spectral Clustering via Sampling: A Review
- Community Detection and Stochastic Block Models
- Least squares quantization in PCM
- Global spectral clustering in dynamic networks
- CONCENTRATION OF RANDOM GRAPHS AND APPLICATION TO COMMUNITY DETECTION
- A Survey of Statistical Network Models
- Statistical Clustering of Temporal Networks Through a Dynamic Stochastic Block Model
- Concentration and regularization of random graphs
- Partitioning Well-Clustered Graphs: Spectral Clustering Works!
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