Advances in Differentially-Private Synthetic Data Generation
Differential Privacy (DP) has become the de facto standard for protecting users’ sensitive data in data analysis. Within this field, one of the most challenging problems is private synthetic data generation, which allows high-quality synthetic data to be shared publicly while retaining the original data’s statistical properties. However, worst-case query workloads often face steep computational …