most citedQuantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding

14 citations · 14 across the 1 of their papers we have counts for

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1 paper

cs.CR2023★ 14 cited

Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding

Yuke Hu, Wei Liang, Ruofan Wu +5

Knowledge Graph Embedding (KGE) is a fundamental technique that extracts expressive representation from knowledge graph (KG) to facilitate diverse downstream tasks. The emerging fe…