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GraphPAS: Parallel Architecture Search for Graph Neural Networks

Published: 11 July 2021 Publication History

Abstract

Graph neural architecture search has received a lot of attention as Graph Neural Networks (GNNs) has been successfully applied on the non-Euclidean data recently. However, exploring all possible GNNs architectures in the huge search space is too time-consuming or impossible for big graph data. In this paper, we propose a parallel graph architecture search (GraphPAS) framework for graph neural networks. In GraphPAS, we explore the search space in parallel by designing a sharing-based evolution learning, which can improve the search efficiency without losing the accuracy. Additionally, architecture information entropy is adopted dynamically for mutation selection probability, which can reduce space exploration. The experimental result shows that GraphPAS outperforms state-of-art models with efficiency and accuracy simultaneously.

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  • (2024)CommGNAS: Unsupervised Graph Neural Architecture Search for Community DetectionIEEE Transactions on Emerging Topics in Computing10.1109/TETC.2023.327018112:2(444-454)Online publication date: Apr-2024
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  • (2024)Depth-adaptive graph neural architecture search for graph classificationKnowledge-Based Systems10.1016/j.knosys.2024.112321301(112321)Online publication date: Oct-2024
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    cover image ACM Conferences
    SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
    July 2021
    2998 pages
    ISBN:9781450380379
    DOI:10.1145/3404835
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 11 July 2021

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    Author Tags

    1. graph neural networks
    2. neural architecture search
    3. parallel search

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    Overall Acceptance Rate 792 of 3,983 submissions, 20%

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    Cited By

    View all
    • (2024)CommGNAS: Unsupervised Graph Neural Architecture Search for Community DetectionIEEE Transactions on Emerging Topics in Computing10.1109/TETC.2023.327018112:2(444-454)Online publication date: Apr-2024
    • (2024)AutoDDI: Drug–Drug Interaction Prediction With Automated Graph Neural NetworkIEEE Journal of Biomedical and Health Informatics10.1109/JBHI.2024.334957028:3(1773-1784)Online publication date: Mar-2024
    • (2024)Depth-adaptive graph neural architecture search for graph classificationKnowledge-Based Systems10.1016/j.knosys.2024.112321301(112321)Online publication date: Oct-2024
    • (2023)Adaptive graph contrastive learning with joint optimization of data augmentation and graph encoderKnowledge and Information Systems10.1007/s10115-023-01979-366:3(1657-1681)Online publication date: 12-Oct-2023
    • (2023)GM2NAS: multitask multiview graph neural architecture searchKnowledge and Information Systems10.1007/s10115-023-01886-765:10(4021-4054)Online publication date: 15-May-2023
    • (2022)Heterogeneous Information Network-Based Recommendation with Metapath Search and Memory Network Architecture SearchMathematics10.3390/math1016289510:16(2895)Online publication date: 12-Aug-2022
    • (2022)Designing the Topology of Graph Neural Networks: A Novel Feature Fusion PerspectiveProceedings of the ACM Web Conference 202210.1145/3485447.3512185(1381-1391)Online publication date: 25-Apr-2022
    • (2022)Multi-View Graph Neural Architecture Search for Biomedical Entity and Relation ExtractionIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2022.320511320:2(1221-1233)Online publication date: 8-Sep-2022
    • (2022)AutoMSR: Auto Molecular Structure Representation Learning for Multi-label Metabolic Pathway PredictionIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2022.319811920:6(3430-3439)Online publication date: 22-Aug-2022
    • (2022)Research on Algorithm of Intelligent Keyboard Routing Based on Line Priority Strategy2022 3rd International Conference on Information Science, Parallel and Distributed Systems (ISPDS)10.1109/ISPDS56360.2022.9874023(386-389)Online publication date: 22-Jul-2022
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