The authors apply the Adaptive Iterative Mechanism to create differentially private synthetic data from the LEMURS wearable and survey dataset and show that epsilon=5 retains useful predictive performance for downstream tasks.
Deep learning with differential privacy,
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Aim High, Stay Private: Differentially Private Synthetic Data Enables Public Release of Behavioral Health Information with High Utility
The authors apply the Adaptive Iterative Mechanism to create differentially private synthetic data from the LEMURS wearable and survey dataset and show that epsilon=5 retains useful predictive performance for downstream tasks.