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Publications [#330134] of Alessandro Arlotto

Papers Published

  1. Arlotto, A; Wei, Y; Xie, X, An adaptive O(log n)-optimal policy for the online selection of a monotone subsequence from a random sample, Random Structures & Algorithms, vol. 52 no. 1 (January, 2018), pp. 41-53, Wiley [doi]
    (last updated on 2018/11/15)

    © 2017 Wiley Periodicals, Inc. Given a sequence of n independent random variables with common continuous distribution, we propose a simple adaptive online policy that selects a monotone increasing subsequence. We show that the expected number of monotone increasing selections made by such a policy is within (Figure presented.) of optimal. Our construction provides a direct and natural way for proving the (Figure presented.) -optimality gap. An earlier proof of the same result made crucial use of a key inequality of Bruss and Delbaen [5] and of de-Poissonization.
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