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"Private, Efficient, and Accurate: Protecting Models Trained by Multi-party ..."

Wenqiang Ruan et al. (2023)

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DOI: 10.1109/SP46215.2023.10179422

access: closed

type: Conference or Workshop Paper

metadata version: 2023-08-25

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  - conf/sp/RuanXFWWH23
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Wenqiang Ruan, Mingxin Xu, Wenjing Fang, Li Wang, Lei Wang, Weili Han:
Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy. SP 2023: 1926-1943

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