# Multilayer hypergraph clustering using the aggregate similarity matrix

arXiv: https://arxiv.org/abs/2301.11657 · HTML: https://mlsanity.com/paper/2301.11657/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 20 of its 39 references that are in the map.
- First posted on arXiv 27 Jan 2023.

## Builds on (most cited first, 20 of 20)

- [Community Detection and Stochastic Block Models](https://mlsanity.com/paper/1703.10146/) (2017)
- [Multilayer Networks](https://mlsanity.com/paper/1309.7233/) (2013)
- [Achieving Exact Cluster Recovery Threshold via Semidefinite Programming](https://mlsanity.com/paper/1412.6156/) (2014)
- [Community Detection for Hypergraph Networks via Regularized Tensor Power Iteration](https://mlsanity.com/paper/1909.06503/) (2019)
- [Consistency of Spectral Hypergraph Partitioning under Planted Partition Model](https://mlsanity.com/paper/1505.01582/) (2015)
- [Stochastic Block Model for Hypergraphs: Statistical limits and a semidefinite programming approach](https://mlsanity.com/paper/1807.02884/) (2018)
- [Hypergraph Spectral Clustering in the Weighted Stochastic Block Model](https://mlsanity.com/paper/1805.08956/) (2018)
- [Community Detection in Hypergraphs, Spiked Tensor Models, and Sum-of-Squares](https://mlsanity.com/paper/1705.02973/) (2017)
- [Spectral Detection on Sparse Hypergraphs](https://mlsanity.com/paper/1507.04113/) (2015)
- [Exact Recovery in the General Hypergraph Stochastic Block Model](https://mlsanity.com/paper/2105.04770/) (2021)
- [Spectral clustering in the dynamic stochastic block model](https://mlsanity.com/paper/1705.01204/) (2017)
- [Community Detection in General Hypergraph via Graph Embedding](https://mlsanity.com/paper/2103.15035/) (2021)
- [On the Minimax Misclassification Ratio of Hypergraph Community Detection](https://mlsanity.com/paper/1802.00926/) (2018)
- [Community detection in the sparse hypergraph stochastic block model](https://mlsanity.com/paper/1904.05981/) (2019)
- [Exact Recovery in the Hypergraph Stochastic Block Model: a Spectral Algorithm](https://mlsanity.com/paper/1811.06931/) (2018)
- [Hypergraph Artificial Benchmark for Community Detection (h-ABCD)](https://mlsanity.com/paper/2210.15009/) (2022)
- [Robust Hypergraph Clustering via Convex Relaxation of Truncated MLE](https://mlsanity.com/paper/2003.10038/) (2020)
- [Community recovery in non-binary and temporal stochastic block models](https://mlsanity.com/paper/2008.04790/) (2020)
- [Sparse random hypergraphs: Non-backtracking spectra and community detection](https://mlsanity.com/paper/2203.07346/) (2022)
- [Model-based clustering in simple hypergraphs through a stochastic blockmodel](https://mlsanity.com/paper/2210.05983/) (2022)

## Built on by (most cited first, 2 of 2)

- [Information-Theoretic Limits and Strong Consistency on Binary Non-uniform Hypergraph Stochastic Block Models](https://mlsanity.com/paper/2306.06845/) (2023)
- [Consistent line clustering using geometric hypergraphs](https://mlsanity.com/paper/2505.24868/) (2025)

## Abstract (arXiv)

We consider the community recovery problem on a multilayer variant of the hypergraph stochastic block model (HSBM). Each layer is associated with an independent realization of a d-uniform HSBM on N vertices. Given the similarity matrix containing the aggregated number of hyperedges incident to each pair of vertices, the goal is to obtain a partition of the N vertices into disjoint communities. In this work, we investigate a semidefinite programming (SDP) approach and obtain information-theoretic conditions on the model parameters that guarantee exact recovery both in the assortative and the disassortative cases.