A O(logn)-OPTIMAL POLICY FOR THE ONLINE SELECTION OF A MONOTONE SUBSEQUENCE FROM A RANDOM SAMPLE
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چکیده
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 policy is within O(logn) of optimal. Our construction provides a direct and natural way for proving the O(logn)-optimality gap. An earlier proof of the same result made crucial use of a key inequality of Bruss and Delbaen (2001) and of de-Poissonization.
منابع مشابه
An adaptive O(log n)-optimal policy for the online selection of a monotone subsequence from a random sample
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 O(logn) of optimal. Our construction provides a direct and natural way for proving the O(logn)-optimality gap. An earli...
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تاریخ انتشار 2016