Refined Asymptotics in the Online Selection of an Increasing Subsequence
Optimization and Control
2018-08-21 v1
Abstract
Let be the maximum expected length of an increasing subsequence, which can be selected by an online nonanticipating policy from a random sample of size . Refining known estimates, we obtain an asymptotic expansion of up to a term. The method we use is based on detailed analysis of the dynamic programming equation, and is also applicable to the online selection problem with observations occurring at times of a Poisson process.
Keywords
Cite
@article{arxiv.1808.06300,
title = {Refined Asymptotics in the Online Selection of an Increasing Subsequence},
author = {Amirlan Seksenbayev},
journal= {arXiv preprint arXiv:1808.06300},
year = {2018}
}
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11 pages