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DGC: Training Dynamic Graphs with Spatio-Temporal Non-Uniformity using Graph Partitioning by Chunks
Although DGNN has recently received considerable attention by AI community and various DGNN models have been proposed, building a distributed system for efficient DGNN training is still challenging.
FedGraph: Federated Graph Learning with Intelligent Sampling
In this paper, we propose FedGraph for federated graph learning among multiple computing clients, each of which holds a subgraph.
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