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Unsupervised learning with GNNs for QUBO-based combinatorial optimization
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DOI：10.1016/j.ejco.2025.100116.png)
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Abstract
En 中文
• Previously suggested GNNsolver is effective on sparse graphs only. • Replacing Adam with RPROP reduced solution times. • GraphSAGE can handle denser graphs, GCN performs better on sparse graphs. • Transfer learning between MaxCut and MIS problems improves solvers performance.
Keywords:
Unsupervised learning
GNNs
QUBO
Maximum cut
Maximum independent set
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