Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering

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》资源》论文》Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering

Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering

2020-03-16 |

66 |

48 |

Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering
论文

Abstract

We introduce submodular hypergraphs, a family of hypergraphs that have different submodular weights associated with different cuts of hyperedges. Submodular hypergraphs arise in clustering applications in which higher-order structures carry relevant information. For such hypergraphs, we define the notion of p-Laplacians and derive corresponding nodal domain theorems and k-way Cheeger inequalities. We conclude with the description of algorithms for computing the spectra of 1and 2-Laplacians that constitute the basis o new spectral hypergraph clustering methods.

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