IGLU: Efficient GCN Training via Lazy Updates

28 September 2021

Papers citing "IGLU: Efficient GCN Training via Lazy Updates"

6 / 6 papers shown

Title
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation Jiong Zhu Aishwarya N. Reganti E-Wen Huang Charles Dickens Nikhil S. Rao Karthik Subbian Danai Koutra GNN FedML 32 3 0 17 May 2023
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations Zirui Liu Sheng-Wei Chen Kaixiong Zhou Daochen Zha Xiao Huang Xia Hu 29 14 0 19 Oct 2022
Graph Generative Model for Benchmarking Graph Neural Networks Minji Yoon Yue Wu John Palowitch Bryan Perozzi Ruslan Salakhutdinov 17 7 0 10 Jul 2022
Transformers from an Optimization Perspective Yongyi Yang Zengfeng Huang David Wipf 37 24 0 27 May 2022
L $^2$ -GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks Yuning You Tianlong Chen Zhangyang Wang Yang Shen GNN 101 82 0 30 Mar 2020
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 169 1,078 0 13 Feb 2020