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...

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書目詳細資料
Main Authors: Zhu, Huafei, Goh, Rick Siow Mong, Ng, Wee Keong
其他作者: School of Computer Science and Engineering
格式: Article
語言:English
出版: 2021
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在線閱讀:https://hdl.handle.net/10356/145818
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