Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks

24 June 2020

Papers citing "Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks"

4 / 4 papers shown

Title
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation Rui Xue Haoyu Han MohamadAli Torkamani Jian Pei Xiaorui Liu GNN 17 18 0 03 Feb 2023
BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling Cheng Wan Youjie Li Ang Li Namjae Kim Yingyan Lin GNN 21 75 0 21 Mar 2022
On Provable Benefits of Depth in Training Graph Convolutional Networks Weilin Cong M. Ramezani M. Mahdavi 16 73 0 28 Oct 2021
Sampling methods for efficient training of graph convolutional networks: A survey Xin Liu Mingyu Yan Lei Deng Guoqi Li Xiaochun Ye Dongrui Fan GNN 21 95 0 10 Mar 2021