mlsanityData to 7 Oct 2026

Finding Bipartite Components in Hypergraphs

arXiv 2205.02771 ↗First posted 5 May 2022cs.DS cs.LGcited by 4

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Abstract (arXiv)

Hypergraphs are important objects to model ternary or higher-order relations of objects, and have a number of applications in analysing many complex datasets occurring in practice. In this work we study a new heat diffusion process in hypergraphs, and employ this process to design a polynomial-time algorithm that approximately finds bipartite components in a hypergraph. We theoretically prove the performance of our proposed algorithm, and compare it against the previous state-of-the-art through extensive experimental analysis on both synthetic and real-world datasets. We find that our new algorithm consistently and significantly outperforms the previous state-of-the-art across a wide range of hypergraphs.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 12 of its 40 references that are in the map. First posted on arXiv 5 May 2022.

Builds on

12 of 40 references.

References · 12

  1. 2019Heterogeneous Graph Attention Networkcited by 732
  2. 2018Solving Linear Programs in the Current Matrix Multiplication Timecited by 100
  3. 2019Random Walks on Hypergraphs with Edge-Dependent Vertex Weightscited by 45
  4. 2019A Deterministic Linear Program Solver in Current Matrix Multiplication Timecited by 42
  5. 2017Inhomogeneous Hypergraph Clustering with Applicationscited by 31
  6. 2014Heat kernel based community detectioncited by 30
  7. 2018Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clusteringcited by 25
  8. 2020p-Norm Flow Diffusion for Local Graph Clusteringcited by 15
  9. 2020Hypergraph Clustering Based on PageRankcited by 15
  10. 2017Cheeger Inequalities for Submodular Transformationscited by 13
  11. 2021Local Hyper-Flow Diffusioncited by 8
  12. 2021Local Algorithms for Finding Densely Connected Clusterscited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 0; 2024: 0; 2025: 1; 2026: 1.

4 papers.