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- W4380993272 abstract "The value maximization version of the secretary problem is the problem of hiring a candidate with the largest value from a randomly ordered sequence of candidates. In this work, we consider a setting where predictions of candidate values are provided in advance. We propose an algorithm that achieves a nearly optimal value if the predictions are accurate and results in a constant-factor competitive ratio otherwise. We also show that the worst-case competitive ratio of an algorithm cannot be higher than some constant $< 1/mathrm{e}$, which is the best possible competitive ratio when we ignore predictions, if the algorithm performs nearly optimally when the predictions are accurate. Additionally, for the multiple-choice secretary problem, we propose an algorithm with a similar theoretical guarantee. We empirically illustrate that if the predictions are accurate, the proposed algorithms perform well; meanwhile, if the predictions are inaccurate, performance is comparable to existing algorithms that do not use predictions." @default.
- W4380993272 created "2023-06-17" @default.
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- W4380993272 date "2023-06-14" @default.
- W4380993272 modified "2023-09-25" @default.
- W4380993272 title "The Secretary Problem with Predictions" @default.
- W4380993272 doi "https://doi.org/10.1287/moor.2022.0031" @default.
- W4380993272 hasPublicationYear "2023" @default.
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