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Prophet Inequalities with Linear Correlations and Augmentations

Published: 13 July 2020 Publication History

Abstract

In a classical online decision problem, a decision-maker who is trying to maximize her value inspects a sequence of arriving items to learn their values (drawn from known distributions), and decides when to stop the process by taking the current item. The goal is to prove a "prophet inequality": that she can do approximately as well as a prophet with foreknowledge of all the values. In this work, we investigate this problem when the values are allowed to be correlated. Since non-trivial guarantees are impossible for arbitrary correlations, we consider a natural "linear" correlation structure introduced by Bateni et al. [ESA'15] as a generalization of the common-base value model of Chawla et al. [GEB'15].
A key challenge is that threshold-based algorithms, which are commonly used for prophet inequalities, no longer guarantee good performance for linear correlations. We relate this roadblock to another "augmentations" challenge that might be of independent interest: many existing prophet inequality algorithms are not robust to slight increase in the values of the arriving items. We leverage this intuition to prove bounds (matching up to constant factors) that decay gracefully with the amount of correlation of the arriving items. We extend these results to the case of selecting multiple items by designing a new $(1+o(1))$ approximation ratio algorithm that is robust to augmentations.

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  • (2024)Prophet Inequalities with Cancellation CostsProceedings of the 56th Annual ACM Symposium on Theory of Computing10.1145/3618260.3649786(1247-1258)Online publication date: 10-Jun-2024
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  • (2024)Pairwise-Independent Contention ResolutionInteger Programming and Combinatorial Optimization10.1007/978-3-031-59835-7_15(196-209)Online publication date: 22-May-2024
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cover image ACM Conferences
EC '20: Proceedings of the 21st ACM Conference on Economics and Computation
July 2020
937 pages
ISBN:9781450379755
DOI:10.1145/3391403
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 13 July 2020

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Author Tags

  1. online algorithms
  2. posted price mechanisms
  3. robust stopping time algorithms

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  • Research-article

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  • Schmidt Foundation

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EC '20
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EC '20: The 21st ACM Conference on Economics and Computation
July 13 - 17, 2020
Virtual Event, Hungary

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Overall Acceptance Rate 664 of 2,389 submissions, 28%

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Cited By

View all
  • (2024)Prophet Inequalities with Cancellation CostsProceedings of the 56th Annual ACM Symposium on Theory of Computing10.1145/3618260.3649786(1247-1258)Online publication date: 10-Jun-2024
  • (2024)Limitations of Stochastic Selection Problems with Pairwise Independent PriorsProceedings of the 56th Annual ACM Symposium on Theory of Computing10.1145/3618260.3649718(479-490)Online publication date: 10-Jun-2024
  • (2024)Pairwise-Independent Contention ResolutionInteger Programming and Combinatorial Optimization10.1007/978-3-031-59835-7_15(196-209)Online publication date: 22-May-2024
  • (2023)SIGACT News Online Algorithms Column 40ACM SIGACT News10.1145/3586165.358617754:1(90-104)Online publication date: 28-Feb-2023
  • (2022)Relaxing the Independence Assumption in Sequential Posted Pricing, Prophet Inequality, and Random Bipartite MatchingWeb and Internet Economics10.1007/978-3-030-94676-0_8(131-148)Online publication date: 1-Jan-2022
  • (undefined)Fair Dynamic RationingSSRN Electronic Journal10.2139/ssrn.3775895

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