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Autori principali: Starr, Shannon, Wu, Erik
Natura: Preprint
Pubblicazione: 2023
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Accesso online:https://arxiv.org/abs/2312.17705
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author Starr, Shannon
Wu, Erik
author_facet Starr, Shannon
Wu, Erik
contents The distribution for the minimum of Brownian motion or the Cauchy process is well-known using the reflection principle. Here we consider the problem of finding the sample-by-sample minimum, which we call the online minimum search. We consider the possibility of the golden search method, but we show quantitatively that the bisection method is more efficient. In the bisection method there is a hierarchical parameter, which tunes the depth to which each sub-search is conducted, somewhat similarly to how a depth-first search works to generate a topological ordering on nodes. Finally, we consider the possibility of using harmonic measure, which is a novel idea that has so far been unexplored.
format Preprint
id arxiv_https___arxiv_org_abs_2312_17705
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Online minimum search for Brownian motion and the Cauchy process: Multiple approaches
Starr, Shannon
Wu, Erik
Probability
Statistics Theory
37H05, 62M45
The distribution for the minimum of Brownian motion or the Cauchy process is well-known using the reflection principle. Here we consider the problem of finding the sample-by-sample minimum, which we call the online minimum search. We consider the possibility of the golden search method, but we show quantitatively that the bisection method is more efficient. In the bisection method there is a hierarchical parameter, which tunes the depth to which each sub-search is conducted, somewhat similarly to how a depth-first search works to generate a topological ordering on nodes. Finally, we consider the possibility of using harmonic measure, which is a novel idea that has so far been unexplored.
title Online minimum search for Brownian motion and the Cauchy process: Multiple approaches
topic Probability
Statistics Theory
37H05, 62M45
url https://arxiv.org/abs/2312.17705