Covariate-Assisted Community Detection in Multi-Layer Networks
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Publication:6190701
DOI10.1080/07350015.2022.2085726OpenAlexW4281717537MaRDI QIDQ6190701
Shirong Xu, Unnamed Author, Junhui Wang
Publication date: 6 March 2024
Published in: Journal of Business & Economic Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/07350015.2022.2085726
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Cites Work
- Unnamed Item
- Tensor Decompositions and Applications
- Fast community detection by SCORE
- Community detection in networks with node features
- Consistent community detection in multi-relational data through restricted multi-layer stochastic blockmodel
- Coauthorship and citation networks for statisticians
- User-friendly tail bounds for sums of random matrices
- Community detection for statistical citation network by D-SCORE
- Community detection with dependent connectivity
- Community detection on mixture multilayer networks via regularized tensor decomposition
- Global and individualized community detection in inhomogeneous multilayer networks
- Null models and community detection in multi-layer networks
- Spectral and matrix factorization methods for consistent community detection in multi-layer networks
- A random effects stochastic block model for joint community detection in multiple networks with applications to neuroimaging
- Consistency of spectral clustering in stochastic block models
- Smallest singular value of a random rectangular matrix
- On the Best Rank-1 and Rank-(R1 ,R2 ,. . .,RN) Approximation of Higher-Order Tensors
- High-Dimensional Probability
- Covariate Regularized Community Detection in Sparse Graphs
- Dimension reduction for covariates in network data
- Latent space models for multiplex networks with shared structure
- Joint latent space models for network data with high-dimensional node variables
- Consistent community detection in multi-layer network data
- A useful variant of the Davis–Kahan theorem for statisticians
- Covariate-assisted spectral clustering
- Community Detection in General Hypergraph Via Graph Embedding
- Bias-Adjusted Spectral Clustering in Multi-Layer Stochastic Block Models