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Erschienen in:

11.12.2023

Non-local Graph Convolutional Network

verfasst von: Chunyu Du, Shuai Shao, Jun Tang, Xinjing Song, Weifeng Liu, Baodi Liu, Yanjiang Wang

Erschienen in: Circuits, Systems, and Signal Processing | Ausgabe 4/2024

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Abstract

Graph convolutional network (GCN) has led to state-of-the-art performance for structured data. The superior performance would be partly due to the convolutional operations that operate over local neighborhoods. However, the distant long-range dependencies in data are still challenging to capture since it requires deep stacks of convolutional operations. Moreover, missing links in structured data might further hurt the performance. This paper introduces non-locality augmented graph convolution blocks into GCN to capture long-range or even disconnected dependencies. Specifically, we propose a dictionary-based non-locality encoding approach in which the non-local information is encoded by both graph convolution and dictionary-based implicit convolution. Unlike previous non-local approaches, our non-local block does not rely on the exhaustive computation of the relationship of data pairs. Thus, it is suitable for GCN, which typically models a large number of data samples. What’s more, the proposed non-local blocks could be embedded into arbitrarily GCN architectures. We demonstrate the efficacy of our non-local block on four benchmark datasets.

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Literatur
26.
40.
Zurück zum Zitat H. You, T. Geng, Y. Zhang, A. Li, Y. Lin, Gcod: Graph convolutional network acceleration via dedicated algorithm and accelerator co-design. In 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA) (IEEE, 2022), pp. 460–474. https://doi.org/10.48550/arXiv.2112.11594 H. You, T. Geng, Y. Zhang, A. Li, Y. Lin, Gcod: Graph convolutional network acceleration via dedicated algorithm and accelerator co-design. In 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA) (IEEE, 2022), pp. 460–474. https://​doi.​org/​10.​48550/​arXiv.​2112.​11594
Metadaten
Titel
Non-local Graph Convolutional Network
verfasst von
Chunyu Du
Shuai Shao
Jun Tang
Xinjing Song
Weifeng Liu
Baodi Liu
Yanjiang Wang
Publikationsdatum
11.12.2023
Verlag
Springer US
Erschienen in
Circuits, Systems, and Signal Processing / Ausgabe 4/2024
Print ISSN: 0278-081X
Elektronische ISSN: 1531-5878
DOI
https://doi.org/10.1007/s00034-023-02563-4