SA-DPSGD: Differentially Private Stochastic Gradient Descent based on Simulated Annealing

Jie Fu, Zhili Chen, XinPeng Ling

Differential privacy (DP) provides a formal privacy guarantee that prevents adversaries with access to machine learning models from extracting information about individual training…