Understanding the Interplay between Privacy and Robustness in Federated Learning

no code implementations • 13 Jun 2021 • Yaowei Han, Yang Cao, Masatoshi Yoshikawa

Federated Learning (FL) is emerging as a promising paradigm of privacy-preserving machine learning, which trains an algorithm across multiple clients without exchanging their data samples.

Adversarial Robustness Federated Learning +1