Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks

16 November 2021

Papers citing "Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks"

20 / 20 papers shown

Title
Enhanced Soups for Graph Neural Networks Joseph Zuber Aishwarya Sarkar Joseph Jennings Ali Jannesari 47 1 0 14 Mar 2025
MassiveGNN: Efficient Training via Prefetching for Massively Connected Distributed Graphs Aishwarya Sarkar Sayan Ghosh Nathan Tallent Ali Jannesari GNN 36 2 0 30 Oct 2024
CATGNN: Cost-Efficient and Scalable Distributed Training for Graph Neural Networks Xin Huang Weipeng Zhuo Minh Phu Vuong Shiju Li Jongryool Kim Bradley Rees Chul-Ho Lee GNN 33 0 0 02 Apr 2024
Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training Charles Dickens E-Wen Huang Aishwarya N. Reganti Jiong Zhu Karthik Subbian Danai Koutra 29 6 0 24 Dec 2023
Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks Nasimeh Heydaribeni Xinrui Zhan Ruisi Zhang Tina Eliassi-Rad F. Koushanfar AI4CE 44 8 0 15 Nov 2023
Distill to Delete: Unlearning in Graph Networks with Knowledge Distillation Yash Sinha Murari Mandal Mohan S. Kankanhalli MU 36 11 0 28 Sep 2023
FedGKD: Unleashing the Power of Collaboration in Federated Graph Neural Networks Qiying Pan Ruofan Wu Tengfei Liu Tianyi Zhang Yifei Zhu Weiqiang Wang FedML 48 9 0 18 Sep 2023
Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction Guangji Bai Ziyang Yu Zheng Chai Yue Cheng Liang Zhao GNN 24 3 0 25 Aug 2023
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware Shichang Zhang Atefeh Sohrabizadeh Cheng Wan Zijie Huang Ziniu Hu Yewen Wang Yingyan Lin Lin Jason Cong Yizhou Sun GNN AI4CE 42 23 0 24 Jun 2023
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication A. Jaiswal Shiwei Liu Tianlong Chen Ying Ding Zhangyang Wang GNN 47 5 0 18 Jun 2023
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 45 3 0 17 May 2023
Boosting Distributed Full-graph GNN Training with Asynchronous One-bit Communication Mengdie Zhang Qi Hu Peng Sun Yonggang Wen Tianwei Zhang GNN 40 5 0 02 Mar 2023
Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection Weilin Cong Mehrdad Mahdavi MU 21 18 0 17 Feb 2023
DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling Md. Vasimuddin Ramanarayan Mohanty Sanchit Misra Sasikanth Avancha GNN 18 1 0 11 Nov 2022
A Comprehensive Survey on Distributed Training of Graph Neural Networks Haiyang Lin Yurui Lai Xiaochun Ye Xiaochun Ye Shirui Pan Wenguang Chen Yuan Xie GNN 38 26 0 10 Nov 2022
Distributed Graph Neural Network Training: A Survey Yingxia Shao Hongzheng Li Xizhi Gu Hongbo Yin Yawen Li Xupeng Miao Wentao Zhang Bin Cui Lei Chen GNN AI4CE 26 56 0 01 Nov 2022
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations Zirui Liu Sheng-Wei Chen Kaixiong Zhou Daochen Zha Xiao Huang Xia Hu 32 15 0 19 Oct 2022
Distributed Graph Neural Network Training with Periodic Stale Representation Synchronization Zheng Chai Guangji Bai Liang Zhao Yue Cheng GNN 30 3 0 31 May 2022
FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks Yuhang Yao Weizhao Jin Yu Yang Carlee Joe-Wong GNN FedML 60 19 0 28 Jan 2022
Deep Graph Generators: A Survey Faezeh Faez Yassaman Ommi M. Baghshah Hamid R. Rabiee GNN AI4CE 53 57 0 31 Dec 2020