Adaptive approximation of the minimum of Brownian motion
Document Type
Article
Publication Date
4-1-2017
Abstract
We study the error in approximating the minimum of a Brownian motion on the unit interval based on finitely many point evaluations. We construct an algorithm that adaptively chooses the points at which to evaluate the Brownian path. In contrast to the 1/2 convergence rate of optimal nonadaptive algorithms, the proposed adaptive algorithm converges at an arbitrarily high polynomial rate.
Identifier
85007549058 (Scopus)
Publication Title
Journal of Complexity
External Full Text Location
https://doi.org/10.1016/j.jco.2016.11.002
e-ISSN
10902708
ISSN
0885064X
First Page
17
Last Page
37
Volume
39
Recommended Citation
Calvin, James M.; Hefter, Mario; and Herzwurm, André, "Adaptive approximation of the minimum of Brownian motion" (2017). Faculty Publications. 9650.
https://digitalcommons.njit.edu/fac_pubs/9650
