Author

Serge Gratton

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Preprint Aug 2026

Two-level domain-decomposition AdaGrad method for scalable training of graph neural networks

The proposed DD-AG2m alternates between AG2m optimization on the original (global) graph and AG2m optimization on the partitioned graphs, and introduces a two-level variant that performs global optimization steps on a coarse graph obtained by randomly subsampling nodes within each subdomain.

Laurynas Varnas, Julien Herrmann, Alexander Heinlein et al. · 0 citations