Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification

Moshe Eliasof, Eldad Haber, Eran Treister

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Graph Neural Networks (GNNs) are prominent in handling sparse and unstructured data efficiently and effectively. Specifically, GNNs were shown to be highly effective for node classification tasks, where labelled information is available for only a fraction of the nodes. Typically, the optimization process, through the objective function, considers only labelled nodes while ignoring the rest. In this paper, we propose novel objective terms for the training of GNNs for node classification, aiming to exploit all the available data and improve accuracy. Our first term seeks to maximize the mutual information between node and label features, considering both labelled and unlabelled nodes in the optimization process. Our second term promotes anisotropic smoothness in the prediction maps. Lastly, we propose a cross-validating gradients approach to enhance the learning from labelled data. Our proposed objectives are general and can be applied to various GNNs, and require no architectural modifications. Extensive experiments demonstrate our approach using popular GNNs like Graph Convolutional Networks (e.g., GCN and GCNII), and Graph Attention Networks (e.g., GAT), reading a consistent and significant accuracy improvement on 10 real-world node classification datasets.

Original languageAmerican English
Title of host publicationECAI 2024 - 27th European Conference on Artificial Intelligence, Including 13th Conference on Prestigious Applications of Intelligent Systems, PAIS 2024, Proceedings
EditorsUlle Endriss, Francisco S. Melo, Kerstin Bach, Alberto Bugarin-Diz, Jose M. Alonso-Moral, Senen Barro, Fredrik Heintz
PublisherIOS Press BV
Pages2508-2515
Number of pages8
ISBN (Electronic)9781643685489
DOIs
StatePublished - 16 Oct 2024
Event27th European Conference on Artificial Intelligence, ECAI 2024 - Santiago de Compostela, Spain
Duration: 19 Oct 202424 Oct 2024

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume392

Conference

Conference27th European Conference on Artificial Intelligence, ECAI 2024
Country/TerritorySpain
CitySantiago de Compostela
Period19/10/2424/10/24

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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