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20162025
most citedLocal2Global: Scaling global representation learning on graphs via local training

2 citations · 4 across the 4 of their papers we have counts for

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cs.LG2022

Local2Global: A distributed approach for scaling representation learning on graphs

Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong +2

We propose a decentralised "local2global"' approach to graph representation learning, that one can a-priori use to scale any embedding technique. Our local2global approach proceeds…