The paper constructs a deterministic one-max-search algorithm that simultaneously achieves the best possible consistency-robustness trade-off and the best possible smoothness for prediction errors, for both multiplicative and additive error definitions.
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Pareto-Optimality, Smoothness, and Stochasticity in Learning-Augmented One-Max-Search
The paper constructs a deterministic one-max-search algorithm that simultaneously achieves the best possible consistency-robustness trade-off and the best possible smoothness for prediction errors, for both multiplicative and additive error definitions.