Learning to Cover Locally: Graph Neural Combinatorial Optimization under a Hard Information Horizon
Neural combinatorial optimization typically assumes a centralized solver that reads the whole instance. We study the opposite: combinatorial optimization under a hard information horizon, where every node commits to its share of a global solution seeing only its $k$-hop neighborhood, and those…
By Johannes F. Loevenich, Thies Moehlenhof, Laurin Holz, Maxime Schwarzer, Tobias Huerten, Roberto Rigolin F. LopesarXiv - stat.ML
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Originally published by arXiv - stat.ML on Oct 2, 2026.
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