Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation. (arXiv:2203.09553v1 [cs.AI])

Federated Learning (FL) on knowledge graphs (KGs) has yet to be as well
studied as other domains, such as computer vision and natural language
processing. A recent study FedE first proposes an FL framework that shares
entity embeddings of KGs across all clients. However, compared with model
sharing in vanilla FL, entity embedding sharing from FedE would incur severe
privacy leakage. Specifically, the known entity embedding can be used to infer
whether a specific relation between two entities exists in …

ai arxiv embedding federated learning graphs knowledge knowledge graphs learning privacy