Differentially private synthetic data generation for robust information fusion

Cai Xiaohong, Yi Sun, Zhaowen Lin, Ripeng Li, Tianwei Cai

Abstract: Highlights•The framework for private synthetic data generation and utilization in information fusion.•Differential privacy of singular values of weight increments ensures privacy of entire matrix.•Updating both important weights and biases enhance differentially private model performance.