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Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model
Differentially private (DP) synthetic data enables the use of sensitive datasets while providing strong privacy guarantees. Recently, Private Evolution (PE) has emerged as a promising framework for generating DP synthetic data using only inference APIs of foundation models. However, suitable foundat
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