Daniel J. Wu

Scalable Differential Privacy With Sparse Network Finetuning

We propose a novel method for privacy-preserving training of deep neural networks leveraging public, out-domain data. While differential privacy (DP) has emerged as a mechanism to protect sensitive data in training datasets, its application to complex visual recognition tasks remains challenging. Tr…