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.
Integrated condi tional estimation-optimization
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Establishes equivalence conditions between nested and joint risk assessments in contextual optimization, shows policy independence from contextual risk measure under conditions, and proves SAA consistency in RKHS.
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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.
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Risk-averse Decision Making with Contextual Information: Model, Sample Average Approximation, and Kernelization
Establishes equivalence conditions between nested and joint risk assessments in contextual optimization, shows policy independence from contextual risk measure under conditions, and proves SAA consistency in RKHS.