Optimization
EfficientNonmyopicBayesianOptimizationvia One-ShotMulti-StepTrees
Neural Information Processing Systems
Most of the existing acquisition policies are only one-step optimal, that is, optimal if the decision horizonwereone.
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Learning-AugmentedApproximationAlgorithmsfor MaximumCutandRelatedProblems
Neural Information Processing Systems
In this paper, we study the role of machine-learned predictions inofflineNP-hard problems. For offline problems, an algorithm has no information disadvantage compared to an optimal solution: thedisadvantage iscomputational.
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