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Federated Knowledge Graphs Embedding
[article]
2021
arXiv
pre-print
In this paper, we propose a novel decentralized scalable learning framework, Federated Knowledge Graphs Embedding (FKGE), where embeddings from different knowledge graphs can be learnt in an asynchronous and peer-to-peer manner while being privacy-preserving. FKGE exploits adversarial generation between pairs of knowledge graphs to translate identical entities and relations of different domains into near embedding spaces. In order to protect the privacy of the training data, FKGE further
arXiv:2105.07615v1
fatcat:il5oopbv65cuzhtyk4ciyqr74u