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Found 2 papers, 1 papers with code
Evaluating Privacy Leakage in Split Learning
In particular, on-device machine learning allows us to avoid sharing raw data with a third-party server during inference.
On the Importance of Difficulty Calibration in Membership Inference Attacks
The vulnerability of machine learning models to membership inference attacks has received much attention in recent years.
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