Asynchronous Byzantine Federated Learning

We propose an asynchronous, Byzantine-resilient FL algorithm that avoids straggler delays and requires no server dataset. By updating after a safe number of client contributions, it outperforms state-of-the-art methods, achieving faster training and higher accuracy under multiple attack types.

Flat Multi-Server

Asynchronous Multi-Server Federated Learning for Geo-Distributed Clients

Spyker is the first fully asynchronous multi-server FL system, eliminating server idle time and single-server bottlenecks. Clients communicate only with their nearest server, while servers also update each other asynchronously. This continuously active design improves scalability and performance across MNIST, CIFAR-10, and WikiText-2.