Moderate deviations for recursive stochastic algorithms
Probability
2014-01-24 v1
Abstract
We prove a moderate deviation principle for the continuous time interpolation of discrete time recursive stochastic processes. The methods of proof are somewhat different from the corresponding large deviation result, and in particular the proof of the upper bound is more complicated. The results can be applied to the design of accelerated Monte Carlo algorithms for certain problems, where schemes based on moderate deviations are easier to construct and in certain situations provide performance comparable to those based on large deviations.
Cite
@article{arxiv.1401.6055,
title = {Moderate deviations for recursive stochastic algorithms},
author = {Paul Dupuis and Dane Johnson},
journal= {arXiv preprint arXiv:1401.6055},
year = {2014}
}
Comments
Submitted to Stochastic Systems