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CCS2025顶会

SCOPE: Expanding Client-Side Post-Processing for Efficient Privacy-Preserving Model Inference

Shenchen Zhu, Kai Chen, Yue Zhao, Cheng'an Wei

2025年份

摘要

Privacy-Preserving Inference (PPI) enables users to leverage powerful machine learning models without revealing sensitive input data. However, existing state-of-the-art solutions remain impractical due to significant computation and communication overheads.

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