most citedClient Adaptation improves Federated Learning with Simulated Non-IID Clients

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.LG2020★ 2 cited

Client Adaptation improves Federated Learning with Simulated Non-IID Clients

Laura Rieger, Rasmus M. Th. Høegh, Lars K. Hansen

We present a federated learning approach for learning a client adaptable, robust model when data is non-identically and non-independently distributed (non-IID) across clients. By s…