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A federated learning differential privacy algorithm for non-Gaussian heterogeneous data
Multi-center heterogeneous data are a hot topic in federated learning. The data of clients and centers do not follow a normal distribution, posing significant challenges to learning. Based on the assumption that the client data have a multivariate skewed normal distribution, we improve the DP-Fed-mv...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10086009/ https://www.ncbi.nlm.nih.gov/pubmed/37037886 http://dx.doi.org/10.1038/s41598-023-33044-y |