Differentially Private Data Generative Models

no code implementations • 6 Dec 2018 • Qingrong Chen, Chong Xiang, Minhui Xue, Bo Li, Nikita Borisov, Dali Kaarfar, Haojin Zhu

We conjecture that the key to defend against the model inversion and GAN-based attacks is not due to differential privacy but the perturbation of training data.

BIG-bench Machine Learning Federated Learning +2