Advancing GraphSAGE with A Data-Driven Node Sampling

29 Apr 2019Jihun OhKyunghyun ChoJoan Bruna

As an efficient and scalable graph neural network, GraphSAGE has enabled an inductive capability for inferring unseen nodes or graphs by aggregating subsampled local neighborhoods and by learning in a mini-batch gradient descent fashion. The neighborhood sampling used in GraphSAGE is effective in order to improve computing and memory efficiency when inferring a batch of target nodes with diverse degrees in parallel... (read more)

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