Cheeger Inequalities for Directed Graphs and Hypergraphs using Reweighted Eigenvalues
Lap Chi Lau, Kam Chuen Tung, Robert Wang
摘要
We derive Cheeger inequalities for directed graphs and hypergraphs using the reweighted eigenvalue approach that was recently developed for vertex expansion in undirected graphs [OZ22, KLT22, JPV22]. The goal is to develop a new spectral theory for directed graphs and an alternative spectral theory for hypergraphs. The first main result is a Cheeger inequality relating the vertex expansion ψ(G) of a directed graph G to the vertex-capacitated maximum reweighted second eigenvalue λ v * 2 that where ∆ is the maximum degree of G. This provides a combinatorial characterization of the fastest mixing time of a directed graph by vertex expansion, and builds a new connection between reweighted eigenvalued, vertex expansion, and fastest mixing time for directed graphs. The second main result is a stronger Cheeger inequality relating the edge conductance φ(G) of a directed graph G to the edge-capacitated maximum reweighted second eigenvalue λ e * 2 that λ e * 2 φ(G) λ e * 2 • log
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引用它的顶会 Paper3
- Fast Algorithms for Directed Graph Partitioning Using Flows and Reweighted EigenvaluesLap Chi Lau, Kam Chuen Tung, Robert WangSODA 2024 · 被引用 2 次
- Fast Algorithms for Hypergraph PageRank with Applications to Semi-Supervised LearningKonstantinos Ameranis, Adela Frances DePavia, Lorenzo Orecchia, Erasmo TaniICML 2024 · 被引用 1 次
- New Approximation Bounds for Small-Set Vertex ExpansionSuprovat Ghoshal, Anand LouisSODA 2024
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- Higher-Order Spectral Clustering of Directed GraphsSteinar Laenen, He SunNeurIPS 2020 · 被引用 33 次
- Near-linear Size Hypergraph Cut SparsifiersYu Chen, Sanjeev Khanna, Ansh NagdaFOCS 2020 · 被引用 15 次
- Spectral Hypergraph Sparsifiers of Nearly Linear SizeMichael Kapralov, Robert Krauthgamer, Jakab Tardos, Yuichi YoshidaFOCS 2021 · 被引用 14 次
- Cheeger Inequalities for Vertex Expansion and Reweighted EigenvaluesTsz Chiu Kwok, Lap Chi Lau, Kam Chuen TungFOCS 2022 · 被引用 5 次
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