Approximate Graph Propagation
Hanzhi Wang, Mingguo He, Zhewei Wei, Sibo Wang, Ye Yuan, Xiaoyong Du, Ji-Rong Wen
Abstract
Efficient computation of node proximity queries such as transition probabilities, Personalized PageRank, and Katz are of fundamental importance in various graph mining and learning tasks. In particular, several recent works leverage fast node proximity computation to improve the scalability of Graph Neural Networks (GNN). However, prior studies on proximity computation and GNN feature propagation are on a case-by-case basis, with each paper focusing on a particular proximity measure.
Topics & Concepts
PageRankComputer scienceScalabilityComputationLeverage (statistics)GraphTheoretical computer scienceCluster analysisNode (physics)Data miningArtificial intelligenceAlgorithmDatabaseStructural engineeringEngineeringAdvanced Graph Neural NetworksStochastic Gradient Optimization TechniquesMachine Learning and Algorithms