DocumentCode
1917189
Title
Adaptive Context Tree Weighting
Author
O´Neill, Alexander ; Hutter, Marcus ; Shao, Wen ; Sunehag, Peter
fYear
2012
fDate
10-12 April 2012
Firstpage
317
Lastpage
326
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
benchmark testing; data compression; encoding; trees (mathematics); adaptive context tree weighting; data compression; input sequence; nonstationary distribution; standard compression benchmark tests; Algorithm design and analysis; Bayesian methods; Context; Data compression; Encoding; History; Prediction algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Compression Conference (DCC), 2012
Conference_Location
Snowbird, UT
ISSN
1068-0314
Print_ISBN
978-1-4673-0715-4
Type
conf
DOI
10.1109/DCC.2012.38
Filename
6189263
Link To Document