GSSNN: Graph Smoothing Splines Neural Networks
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Zhou, Lewei
Pan, Shirui
Zhou, Chuan
Yan, Guiying
Wang, Bin
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Abstract
Graph Neural Networks (GNNs) have achieved state-of-the-art performance in many graph data analysis tasks. However, they still suffer from two limitations for graph representation learning. First, they exploit non-smoothing node features which may result in suboptimal embedding and degenerated performance for graph classification. Second, they only exploit neighbor information but ignore global topological knowledge. Aiming to overcome these limitations simultaneously, in this paper, we propose a novel, flexible, and end-to-end framework, Graph Smoothing Splines Neural Networks (GSSNN), for graph classification. By exploiting the smoothing splines, which are widely used to learn smoothing fitting function in regression, we develop an effective feature smoothing and enhancement module Scaled Smoothing Splines (S3) to learn graph embedding. To integrate global topological information, we design a novel scoring module, which exploits closeness, degree, as well as self-attention values, to select important node features as knots for smoothing splines. These knots can be potentially used for interpreting classification results. In extensive experiments on biological and social datasets, we demonstrate that our model achieves state-of-the-arts and GSSNN is superior in learning more robust graph representations. Furthermore, we show that S3 module is easily plugged into existing GNNs to improve their performance.
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Proceedings of The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20)
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34
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4
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© 2020 AAAI Press. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
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Science & Technology
Social Sciences
Computer Science, Artificial Intelligence
Computer Science, Interdisciplinary Applications
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Zhu, S; Zhou, L; Pan, S; Zhou, C; Yan, G; Bin, W, GSSNN: Graph Smoothing Splines Neural Networks, Proceedings of The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), 2020, 34, pp. 7007-7014