Privacy-preserving weighted federated learning within the secret sharing framework
This paper studies privacy-preserving weighted federated learning within the secret sharing framework, where individual private data is split into random shares which are distributed among a set of pre-defined computing servers. The contribution of this paper mainly comprises the following four-fold...
| Main Authors: | , , |
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| Outros Autores: | |
| Formato: | Journal Article |
| Idioma: | English |
| Publicado em: |
2021
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| Assuntos: | |
| Acesso em linha: | https://hdl.handle.net/10356/145818 |