NPA: Improving Large-scale Graph Neural Networks with Non-parametric Attention-Reference-Cited by-同舟云学术

NPA: Improving Large-scale Graph Neural Networks with Non-parametric Attention

Published:2024-06-09 Issue: Volume:34 Page:414-427
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Container-title:Companion of the 2024 International Conference on Management of Data
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Author:

Zhang Wentao¹^ORCID,Yan Guochen²^ORCID,Shen Yu²^ORCID,Ling Yang²^ORCID,Tao Yangyu³^ORCID,Cui Bin²^ORCID,Tang Jian⁴^ORCID

Affiliation:

1. Center for Machine Learning Research, Peking University, Beijing, China

2. School of Computer Science, Peking University, Beijing, China

3. Tencent Inc., Beijing, China

4. Mila - Québec AI Institute & HEC Montréal, Montreal, Canada

Funder

NSFC

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626246.3653399

Reference50 articles.

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3. Shaofeng Cai, Kaiping Zheng, Gang Chen, H. V. Jagadish, Beng Chin Ooi, and Meihui Zhang. 2021. ARM-Net: Adaptive Relation Modeling Network for Structured Data. In SIGMOD '21: International Conference on Management of Data, Virtual Event, China, June 20--25, 2021. 207--220.

4. Jie Chen Tengfei Ma and Cao Xiao. 2018a. FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling. In ICLR.

5. Jianfei Chen, Jun Zhu, and Le Song. 2018b. Stochastic Training of Graph Convolutional Networks with Variance Reduction. In Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsm"a ssan, Stockholm, Sweden, July 10--15, 2018. 941--949.