Accurate, Efficient and Scalable Graph Embedding accepted at IPDPS ’19

Our paper “Accurate, Efficient and Scalable Graph Embedding” has been accepted as a full paper at IEEE IPDPS ’19. This paper describes a novel sampling-based low-complexity technique for Inductive Learning on Graphs and efficient parallelization of all the steps in the algorithm.