DFedRW runs parallel random walk model updates with decentralized averaging and reports accuracy gains of up to 38 percentage points over FedAvg and DFedAvg under high heterogeneity.
D-cliques: Compensating for data heterogeneity with topology in decentralized federated learning,
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Decentralized Federated Averaging via Random Walk
DFedRW runs parallel random walk model updates with decentralized averaging and reports accuracy gains of up to 38 percentage points over FedAvg and DFedAvg under high heterogeneity.