Adaptive Context Tree Weighting
Data Compression Conference（2012）
摘要
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.
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关键词
adaptive context tree weighting,individual file,standard ctw algorithm,standard context tree weighting,data compression result,actw variant,non-stationary distribution,merged file,input sequence,standard compression benchmark test,benchmark testing,bayesian method,stationary distribution,history,bayesian methods,data compression,algorithm design and analysis,encoding,algorithm design,prediction algorithms
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