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Multi-level Monte Carlo methods have become an established technique in uncertainty quantification as they provide the same statistical accuracy as traditional Monte Carlo methods but with increased computational performance. Recently, similar techniques using multi-level ensembles have been applied...

Federated learning (FL) relies on the frequent exchange of model parameters between clients and the aggregator to achieve efficient model convergence. However, network latency presents a significant challenge, particularly in congested edge/IoT scenarios, hindering the efficiency and effectiveness...