Abstract: Due to the irregular memory access and high bandwidth demanding, graph processing is usually inefficient on conventional computer architectures. The recent development of the ...

Abstract: Federated learning, as a privacy preserving distributed machine learning paradigm, enables geographically dispersed clients to collaboratively train a shared model without exchanging raw ...