Learning while Respecting Privacy and Robustness to Distributional Uncertainties and Adversarial Data

Alireza Sadeghi, Gang Wang, Meng Ma +1

Data used to train machine learning models can be adversarial--maliciously constructed by adversaries to fool the model. Challenge also arises by privacy, confidentiality, or due t…