AutoGL: A Library for Automated Graph Learning

arXiv:2104.04987v4 Announce Type: replace
Abstract: Recent years have witnessed an upsurge in research interests and applications of machine learning on graphs. However, manually designing the optimal machine learning algorithms for different graph datasets and tasks is inflexible, labor-intensive, and requires expert knowledge, limiting its adaptivity and applicability. Automated machine learning (AutoML) on graphs, aiming to automatically design the optimal machine learning algorithm for a given graph dataset and task, has received considerable attention. However, none of the existing libraries can …

arxiv automated cs.ai cs.lg graph graph learning library type