Adaptive Context Tree Weighting
This is an incremental improvement for data compression applications dealing with non-stationary data.
The authors tackled the problem of non-stationary input sequences by extending the context tree weighting algorithm to give more weight to recent observations, resulting in improved data compression performance on merged benchmark files without significant losses on individual files.
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.