On the Relationship between Model Quantization and Model Inversion Attacks
A privacy-aware post-training quantization method that improves inversion resistance while recovering utility is guided, using a Fisher-type task-sensitivity proxy for budget-aware bit allocation, calibrates activation ranges, and jointly optimizes weight and activation scales and weight-rounding decisions.
Rong-Ke Liu, You-Wen Zhu
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