Derives generalization bounds for perturbed surrogate policies in combinatorial optimization by decomposing excess risk into perturbation bias controlled by fan-crossing probability, statistical estimation error, and optimization error.
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Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems
Derives generalization bounds for perturbed surrogate policies in combinatorial optimization by decomposing excess risk into perturbation bias controlled by fan-crossing probability, statistical estimation error, and optimization error.