185,523 research outputs found

    The Returning Secretary

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    In the online random-arrival model, an algorithm receives a sequence of nn requests that arrive in a random order. The algorithm is expected to make an irrevocable decision with regard to each request based only on the observed history. We consider the following natural extension of this model: each request arrives k times, and the arrival order is a random permutation of the kn arrivals; the algorithm is expected to make a decision regarding each request only upon its last arrival. We focus primarily on the case when k=2, which can also be interpreted as each request arriving at, and departing from the system, at a random time. We examine the secretary problem: the problem of selecting the best secretary when the secretaries are presented online according to a random permutation. We show that when each secretary arrives twice, we can achieve a competitive ratio of 0.767974... (compared to 1/e in the classical secretary problem), and that it is optimal. We also show that without any knowledge about the number of secretaries or their arrival times, we can still hire the best secretary with probability at least 2/3, in contrast to the impossibility of achieving a constant success probability in the classical setting. We extend our results to the matroid secretary problem, introduced by Babaioff et al. [3], and show a simple algorithm that achieves a 2-approximation to the maximal weighted basis in the new model (for k=2). We show that this approximation factor can be improved in special cases of the matroid secretary problem; in particular, we give a 16/9-competitive algorithm for the returning edge-weighted bipartite matching problem

    Letter From Francis Mairs Huntington-Wilson to Charles Norton, June 29, 1909

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    The document is a carbon copy of a typed letter from the Assistant Secretary of State to Charles Norton, returning a letter to Norton and replying for the Secretary of State about an invitation.https://digitalcommons.ursinus.edu/fmhw_other/1137/thumbnail.jp

    Modrall Sperling interviews Kevin Washburn about Indian law and returning to New Mexico

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    Reflections on Service as Assistant Secretary-Indian Affairs, the State of Indian Law in 2016, and Returning Home to New Mexic

    Packing Returning Secretaries

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    We study online secretary problems with returns in combinatorial packing domains with nn candidates that arrive sequentially over time in random order. The goal is to accept a feasible packing of candidates of maximum total value. In the first variant, each candidate arrives exactly twice. All 2n2n arrivals occur in random order. We propose a simple 0.5-competitive algorithm that can be combined with arbitrary approximation algorithms for the packing domain, even when the total value of candidates is a subadditive function. For bipartite matching, we obtain an algorithm with competitive ratio at least 0.5721o(1)0.5721 - o(1) for growing nn, and an algorithm with ratio at least 0.54590.5459 for all n1n \ge 1. We extend all algorithms and ratios to k2k \ge 2 arrivals per candidate. In the second variant, there is a pool of undecided candidates. In each round, a random candidate from the pool arrives. Upon arrival a candidate can be either decided (accept/reject) or postponed (returned into the pool). We mainly focus on minimizing the expected number of postponements when computing an optimal solution. An expected number of Θ(nlogn)\Theta(n \log n) is always sufficient. For matroids, we show that the expected number can be reduced to O(rlog(n/r))O(r \log (n/r)), where rn/2r \le n/2 is the minimum of the ranks of matroid and dual matroid. For bipartite matching, we show a bound of O(rlogn)O(r \log n), where rr is the size of the optimum matching. For general packing, we show a lower bound of Ω(nloglogn)\Omega(n \log \log n), even when the size of the optimum is r=Θ(logn)r = \Theta(\log n).Comment: 23 pages, 5 figure

    For Our Information, Winter & June 1964, Vol. XVI, no. 2-3

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    An official publication of the ILR School, Cornell University, “for the information of all faculty, staff and students.
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