PAWL-Forced Simulated Tempering
Computation
2013-05-23 v1 Machine Learning
Abstract
In this short note, we show how the parallel adaptive Wang-Landau (PAWL) algorithm of Bornn et al. (2013) can be used to automate and improve simulated tempering algorithms. While Wang-Landau and other stochastic approximation methods have frequently been applied within the simulated tempering framework, this note demonstrates through a simple example the additional improvements brought about by parallelization, adaptive proposals and automated bin splitting.
Cite
@article{arxiv.1305.5017,
title = {PAWL-Forced Simulated Tempering},
author = {Luke Bornn},
journal= {arXiv preprint arXiv:1305.5017},
year = {2013}
}
Comments
Proceedings of BAYSM, 2013