Adaptive Context Tree Weighting
Information Theory
2012-01-11 v1 Machine Learning
math.IT
Abstract
We describe an adaptive context tree weighting (ACTW) algorithm, as an extension to the standard context tree weighting (CTW) algorithm. Unlike the standard CTW algorithm, which weights all observations equally regardless of the depth, ACTW gives increasing weight to more recent observations, aiming to improve performance in cases where the input sequence is from a non-stationary distribution. Data compression results show ACTW variants improving over CTW on merged files from standard compression benchmark tests while never being significantly worse on any individual file.
Keywords
Cite
@article{arxiv.1201.2056,
title = {Adaptive Context Tree Weighting},
author = {Alexander O'Neill and Marcus Hutter and Wen Shao and Peter Sunehag},
journal= {arXiv preprint arXiv:1201.2056},
year = {2012}
}
Comments
11 LaTeX pages, 7 tables