PrivSynth: Alternating and Control-Based Optimization for Privacy and Utility in Synthetic Data
PrivSynth is proposed, a framework that quantifies multiple privacy risks and integrates it into the control ob-jective, and achieves better utility and stronger privacy protection than state-of-the-art methods.
Xinyuan Zhao, Hanlin Gu, Gui-Bao Song et al.
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