Survey on Optimization in Federated Learning

Explore a comprehensive survey on optimization techniques in Federated Learning (FL) presented by Nati Srebro from Toyota Technological Institute at Chicago. Delve into the intricacies of federated and collaborative learning approaches, gaining valuable insights into cutting-edge optimization strategies used in distributed machine learning environments. Discover how these techniques address challenges unique to FL, such as data privacy, communication efficiency, and heterogeneous data distributions across multiple clients.

Survey on Optimization in FL