March 16, 2022, 1:20 a.m. | Udesh Kumarasinghe, Fatih Deniz, Mohamed Nabeel

cs.CR updates on arXiv.org arxiv.org

In order to advance the state of the art in graph learning algorithms, it is
necessary to construct large real-world datasets. While there are many
benchmark datasets for homogeneous graphs, only a few of them are available for
heterogeneous graphs. Furthermore, the latter graphs are small in size
rendering them insufficient to understand how graph learning algorithms perform
in terms of classification metrics and computational resource utilization. We
introduce, PDNS-Net, the largest public heterogeneous graph dataset containing
447K nodes and …

benchmark large lg network resolutions

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