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A federated graph neural network framework for privacy-preserving personalization
Graph neural network (GNN) is effective in modeling high-order interactions and has been widely used in various personalized applications such as recommendation. However, mainstream personalization methods rely on centralized GNN learning on global graphs, which have considerable privacy risks due t...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9163103/ https://www.ncbi.nlm.nih.gov/pubmed/35654792 http://dx.doi.org/10.1038/s41467-022-30714-9 |