PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions

Understand

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, which may lead to loss of subtle but important structural information within the graph and other dependencies among neighbors.