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FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy. (arXiv:2205.15896v1 [cs.DC])
June 1, 2022, 1:20 a.m. | Qiying Pan (1), Yifei Zhu (1) ((1) Shanghai Jiao Tong University)
cs.CR updates on arXiv.org arxiv.org
Node embedding aims to map nodes in the complex graph into low-dimensional
representations. The real-world large-scale graphs and difficulties of labeling
motivate wide studies of unsupervised node embedding problems. Nevertheless,
previous effort mostly operates in a centralized setting where a complete graph
is given. With the growing awareness of data privacy, data holders who are only
aware of one vertex and its neighbours demand greater privacy protection. In
this paper, we introduce FedWalk, a random-walk-based unsupervised node
embedding algorithm that …
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