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Universal Online Contention Resolution with Preselected Order

Author Junyao Zhao

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ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
Keywords
  • Matroids
  • online contention resolution schemes
  • secretary problems

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Abstract

Online contention resolution scheme (OCRS) is a powerful technique for online decision making, which - in the case of matroids - given a matroid and a prior distribution of active elements, selects a subset of active elements that satisfies the matroid constraint in an online fashion. OCRS has been studied mostly for product distributions in the literature. Recently, universal OCRS, that works even for correlated distributions, has gained interest, because it naturally generalizes the classic notion, and its existence in the random-order arrival model turns out to be equivalent to the matroid secretary conjecture. However, currently very little is known about how to design universal OCRSs for any arrival model. In this work, we consider a natural and relatively flexible arrival model, where the OCRS is allowed to preselect (i.e., non-adaptively select) the arrival order of the elements, and within this model, we design simple and optimal universal OCRSs that are computationally efficient. In the course of deriving our OCRSs, we also discover an efficient reduction from universal online contention resolution to the matroid secretary problem for any arrival model, answering a question posed in [Dughmi, 2020].

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Junyao Zhao. Universal Online Contention Resolution with Preselected Order. In 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 334, pp. 137:1-137:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.ICALP.2025.137

Author Details

Junyao Zhao
  • IRIF, CNRS, Université Paris Cité, Paris, France

Funding

  • Zhao, Junyao: Supported by a postdoctoral fellowship from the Fondation Sciences Mathématiques de Paris. Part of the work was done while the author was a Ph.D. student at Stanford University, where he was supported by NSF CCF-1954927.

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