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相关论文: Optimal stopping in a two-sided secretary problem

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The decision-maker (DM) sequentially evaluates up to N of different, rankable options. DM must select exactly the best one at the moment of its appearance. In the process of searching, DM finds out with each applicant whether she is the…

最优化与控制 · 数学 2022-05-23 Krzysztof J. Szajowski

In the Secretary Problem, one has to hire the best among n candidates. The candidates are interviewed, one at a time, at a random order, and one has to decide on the spot, whether to hire a candidate or continue interviewing. It is well…

数据结构与算法 · 计算机科学 2015-07-23 Moran Feldman , Rani Izsak

We study the secretary problem in which rank-ordered lists are generated by the Mallows model and the goal is to identify the highest-ranked candidate through a sequential interview process which does not allow rejected candidates to be…

统计方法学 · 统计学 2023-03-03 Xujun Liu , Olgica Milenkovic , George V. Moustakides

In the secretary problem we are faced with an online sequence of elements with values. Upon seeing an element we have to make an irrevocable take-it-or-leave-it decision. The goal is to maximize the probability of picking the element of…

计算机科学与博弈论 · 计算机科学 2020-11-17 José Correa , Andrés Cristi , Laurent Feuilloley , Tim Oosterwijk , Alexandros Tsigonias-Dimitriadis

The Sliding Window Secretary Problem allows a window of choices to the Classical Secretary Problem, in which there is the option to choose the previous $K$ choices immediately prior to the current choice. We consider a case of this…

概率论 · 数学 2015-09-01 Shan-Yuan Ho , Abijith Krishnan

The game of best choice (also known as the secretary problem) is a model for sequential decision making with a long history and many variations. The classical setup assumes that the sequence of candidate rankings are uniformly distributed.…

组合数学 · 数学 2019-11-06 Brant Jones

One way to interpret the classical secretary problem (CSP) is to consider it as a special case of the following problem. We observe $n$ independent indicator variables $I_1,I_2,\dotsc,I_n$ sequentially and we try to stop on the last…

概率论 · 数学 2013-09-13 Rémi Dendievel

We consider the secretary problem through the lens of learning-augmented algorithms. As it is known that the best possible expected competitive ratio is $1/e$ in the classic setting without predictions, a natural goal is to design…

数据结构与算法 · 计算机科学 2024-11-05 Davin Choo , Chun Kai Ling

We consider a variant of the secretary problem in which the candidates state their expected salary at the interview, which we assume is in accordance with their qualifications. The goal is for the employer to hire the best or the worst…

概率论 · 数学 2016-03-22 L. Bayon , J. Grau , A. M. Oller-Marcen , M. Ruiz , P. M. Suarez

The prophet and secretary problems demonstrate online scenarios involving the optimal stopping theory. In a typical prophet or secretary problem, selection decisions are assumed to be immediate and irrevocable. However, many online settings…

计算机科学与博弈论 · 计算机科学 2019-11-07 Tomer Ezra , Michal Feldman , Ilan Nehama

We solve the secretary problem in the case that the ranked items arrive in a statistically biased order rather than in uniformly random order. The bias is given by a Mallows distribution with parameter $q\in(0,1)$, so that higher ranked…

概率论 · 数学 2021-12-02 Ross G. Pinsky

In a matroid secretary problem, one is presented with a sequence of objects of various weights in a random order, and must choose irrevocably to accept or reject each item. There is a further constraint that the set of items selected must…

计算机科学与博弈论 · 计算机科学 2013-01-22 David Harris , Manish Purohit

In this paper, we present a novel method for computing the asymptotic values of both the optimal threshold, and the probability of success in sequences of optimal stopping problems. This method, based on the resolution of a first-order…

概率论 · 数学 2022-05-18 L. Bayón , P. Fortuny , J. M. Grau , A. M. Oller-Marcén , M. M. Ruiz

In learning-augmented online algorithms, predictions are usually valued for what they say: a value estimate, a solution, or an algorithmic recommendation. This paper shows that predictions can also be valuable solely due to their arrival…

数据结构与算法 · 计算机科学 2026-05-22 Franziska Eberle , Alexander Lindermayr

The following optimal stopping problem is considered. The vertices of a graph $G$ are revealed one by one, in a random order, to a selector. He aims to stop this process at a time $t$ that maximizes the expected number of connected…

组合数学 · 数学 2021-10-05 Fabrício Siqueira Benevides , Małgorzata Sulkowska

We consider two variants of the secretary problem, the\emph{ Best-or-Worst} and the \emph{Postdoc} problems, which are closely related. First, we prove that both variants, in their standard form with binary payoff 1 or 0, share the same…

概率论 · 数学 2017-06-23 L. Bayon , P. Fortuny Ayuso , J. M. Grau , A. M. Oller-Marcen , M. M. Ruiz

Given integers $1\leq k<n$, the Gusein-Zade version of a generalized secretary problem is to choose one of the $k$ best of $n$ candidates for a secretary, which are interviewing in random order. The stopping rule in the selection is based…

组合数学 · 数学 2016-10-19 Adam Woryna

We solve the secretary problem in the case that the ranked items arrive in a statistically biased order rather than in uniformly random order. The bias is given by the left-to-right-minimum exponentially tilted distribution with parameter…

概率论 · 数学 2023-07-18 Ross G. Pinsky

The secretary problem is one of the fundamental problems in online decision making; a tight competitive ratio for this problem of $1/\mathrm{e} \approx 0.368$ has been known since the 1960s. Much more recently, the study of algorithms with…

数据结构与算法 · 计算机科学 2024-10-01 Alexander Braun , Sherry Sarkar

We study the two-sided stable matching problem with one-sided uncertainty for two sets of agents A and B, with equal cardinality. Initially, the preference lists of the agents in A are given but the preferences of the agents in B are…

数据结构与算法 · 计算机科学 2024-07-16 Evripidis Bampis , Konstantinos Dogeas , Thomas Erlebach , Nicole Megow , Jens Schlöter , Amitabh Trehan