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Utilizing Redundancy in Cost Functions for Resilience in Distributed Optimization and Learning
We demonstrate, both theoretically and empirically, the merits of our proposed redundancy model in improving the robustness of DGD against asynchronous and Byzantine agents, and their extensions to distributed stochastic gradient descent (D-SGD) for robust distributed machine learning with asynchronous and Byzantine agents.
Byzantine Fault-Tolerance in Federated Local SGD under 2f-Redundancy
However, we do not know of any such techniques for the federated local SGD algorithm - a more commonly used method for federated machine learning.
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