Sharp Robust Aggregation in Federated and Distributed Learning: Exact Byzantine Robustness Coefficients, Interactive Communication Lower Bounds, and Compressed Delayed Momentum
This research release develops sharp mathematical results for Byzantine-robust aggregation, exact communication complexity, and compressed delayed momentum in federated and distributed optimization. The work studies a central question in robust distributed learning: how accurately can a server aggregate vectors when up...