PLMA combines cross-graph attention EBMs with short warm-started MCMC chains to reach near-zero average optimality gaps on QAPLIB and strong robustness on hard Taixxeyy instances.
A learning method with gap-aware generation for heterogeneous dag scheduling
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Learning to Solve the Quadratic Assignment Problem with Warm-Started MCMC Finetuning
PLMA combines cross-graph attention EBMs with short warm-started MCMC chains to reach near-zero average optimality gaps on QAPLIB and strong robustness on hard Taixxeyy instances.