Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/115929
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Title: Distributed secretary problem : a case of two uneven queues
Authors: Ding, K 
Li, B 
Wang, F 
Issue Date: 2025
Source: In WWW Companion ’25: Companion Proceedings of the ACM: Web Conference 2025, p. 952-956. New York, NY: The Association for Computing Machinery, 2025
Abstract: Secretary problem is one of the most widely studied online stochastic models, in which an employer wants to hire the best candidate from n candidates who arrive in a random order. It is well-known that the optimal success probability is 1/e. However, in reality, things are more complex because employers often have interviewers in different cities, interviewing candidates in a distributed manner. This motivates us to study the secretary problem with multiple queues. Feldman and Tennenholtz [EC 2012] studied this assuming the candidates are distributed evenly. In particular, when there are two even queues, the optimal success probability is 1/4. In this work, we move to the general problem when the queues are arbitrary and design the optimal online algorithm for the case of two queues. Our results characterize the exact success probability curve, connecting the cases of a single queue and two equal queues. Our technique is grounded on the linear programming framework introduced by Buchbinder et al. [Math. Oper. Res. 2014] and a novel analysis.
Keywords: Linear programming
Multi-queue
Secretary problem
Publisher: The Association for Computing Machinery
ISBN: 979-8-4007-1331-6
DOI: 10.1145/3701716.3715529
Description: WWW '25: The ACM Web Conference 2025, Sydney NSW Australia, 28 April 2025 - 2 May 2025
Rights: This work is licensed under a Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/). WWW Companion ’25, Sydney, NSW, Australia
©2025 Copyright held by the owner/author(s).
The following publication Ding, K., Li, B., & Wang, F. (2025). Distributed Secretary Problem: A Case of Two Uneven Queues Companion Proceedings of the ACM on Web Conference 2025, Sydney NSW, Australia is available at https://doi.org/10.1145/3701716.3715529.
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