PINE : Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence(2022)
摘要
Graph node embedding aims at learning a vector representation for all nodes given a graph. It is a central problem in many machine learning tasks (e.g., node classification, recommendation, community detection). The key problem in graph node embedding lies in how to define the dependence to neighbors. Existing approaches specify (either explicitly or implicitly) certain dependencies on neighbors, ...
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关键词
Task analysis,Laplace equations,Aggregates,Reinforcement learning,Matrix decomposition,Graph neural networks,Games
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