mlsanityData to 14 Oct 2026

ALMA: Alternating Minimization Algorithm for Clustering Mixture Multilayer Network

arXiv 2102.10226 ↗First posted 20 Feb 2021stat.ML cs.LG math.STcited by 8

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Abstract (arXiv)

The paper considers a Mixture Multilayer Stochastic Block Model (MMLSBM), where layers can be partitioned into groups of similar networks, and networks in each group are equipped with a distinct Stochastic Block Model. The goal is to partition the multilayer network into clusters of similar layers, and to identify communities in those layers. Jing et al. (2020) introduced the MMLSBM and developed a clustering methodology, TWIST, based on regularized tensor decomposition. The present paper proposes a different technique, an alternating minimization algorithm (ALMA), that aims at simultaneous recovery of the layer partition, together with estimation of the matrices of connection probabilities of the distinct layers. Compared to TWIST, ALMA achieves higher accuracy both theoretically and numerically.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 22 of its 52 references that are in the map. First posted on arXiv 20 Feb 2021.

Builds on

22 of 52 references.

References · 22

  1. 2017Community Detection and Stochastic Block Modelscited by 319
  2. 2013Consistency of spectral clustering in stochastic block modelscited by 129
  3. 2013Multilayer Networkscited by 87
  4. 2014Layer aggregation and reducibility of multilayer interconnected networkscited by 34
  5. 2020Community Detection on Mixture Multi-layer Networks via Regularized Tensor Decompositioncited by 30
  6. 2017Spectral and matrix factorization methods for consistent community detection in multi-layer networkscited by 27
  7. 2020Exact Clustering in Tensor Block Model: Statistical Optimality and Computational Limitcited by 23
  8. 2019Multiway clustering via tensor block modelscited by 17
  9. 2015Community detection in multi-relational data with restricted multi-layer stochastic blockmodelcited by 14
  10. 2020Latent space models for multiplex networks with shared structurecited by 14
  11. 2018Provable Convex Co-clustering of Tensorscited by 13
  12. 2017Spectral clustering in the dynamic stochastic block modelcited by 12
10 more
  1. 2018Change Point Estimation in a Dynamic Stochastic Block Modelcited by 10
  2. 2020General Community Detection with Optimal Recovery Conditions for Multi-relational Sparse Networks with Dependent Layerscited by 7
  3. 2018Multilayer Networks in a Nutshellcited by 6
  4. 2016General Tensor Spectral Co-clustering for Higher-Order Datacited by 5
  5. 2016Bayesian Learning of Dynamic Multilayer Networkscited by 5
  6. 2017Quantifying layer similarity in multiplex networks: a systematic studycited by 5
  7. 2018The Power Mean Laplacian for Multilayer Graph Clusteringcited by 5
  8. 2017Layer Communities in Multiplex Networkscited by 1
  9. 2018Multiresolution Tensor Decomposition for Multiple Spatial Passing Networkscited by 1
  10. 2018Testing Changes in Communities for the Stochastic Block Modelcited by 1

Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 2; 2024: 2; 2025: 3.

8 papers.

  1. 2022Sparse Subspace Clustering in Diverse Multiplex Network Modelcited by 4
  2. 2023Optimal Clustering of Discrete Mixtures: Binomial, Poisson, Block Models, and Multi-layer Networkscited by 3
  3. 2023Nested stochastic block model for simultaneously clustering networks and nodescited by 1
  4. 2024Signed Diverse Multiplex Networks: Clustering and Inferencecited by 1
  5. 2024Mixture of multilayer stochastic block models for multiview clusteringcited by 0
  6. 2025Perfect Clustering in Very Sparse Diverse Multiplex Networkscited by 0
  7. 2025Simultaneous estimation of connectivity and dimensionality in samples of networkscited by 0
  8. 2025Transfer learning under latent space modelcited by 0