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...

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Detalles Bibliográficos
Autores principales: Yang, Xinyu, Wu, Weisan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
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

Internet

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

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