hypergraph partitioning

6 papers with code • 0 benchmarks • 0 datasets

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Most implemented papers

Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions

elki-project/elki JMLR 2002

We evaluate the effectiveness of cluster ensembles in three qualitatively different application scenarios: (i) where the original clusters were formed based on non-identical sets of features, (ii) where the original clustering algorithms worked on non-identical sets of objects, and (iii) where a common data-set is used and the main purpose of combining multiple clusterings is to improve the quality and robustness of the solution.

Improving Coarsening Schemes for Hypergraph Partitioning by Exploiting Community Structure

SebastianSchlag/kahypar SEA 2017 2017

We present an improved coarsening process for multilevel hypergraph partitioning that incorporates global information about the community structure.

Inhomogeneous Hypergraph Clustering with Applications

lipan00123/InHclustering NeurIPS 2017

Hypergraph partitioning is an important problem in machine learning, computer vision and network analytics.

Co-clustering Vertices and Hyperedges via Spectral Hypergraph Partitioning

yuzhu2019/hypergraph_cocluster 19 Feb 2021

We propose a novel method to co-cluster the vertices and hyperedges of hypergraphs with edge-dependent vertex weights (EDVWs).

HyperSF: Spectral Hypergraph Coarsening via Flow-based Local Clustering

aghdaei/hypersf 17 Aug 2021

To address the ever-increasing computational challenges, graph coarsening can be potentially applied for preprocessing a given hypergraph by aggressively aggregating its vertices (nodes).

HyperEF: Spectral Hypergraph Coarsening by Effective-Resistance Clustering

feng-research/hyperef 26 Oct 2022

This paper introduces a scalable algorithmic framework (HyperEF) for spectral coarsening (decomposition) of large-scale hypergraphs by exploiting hyperedge effective resistances.