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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Context tree weighting | 1/1 | https://en.wikipedia.org/wiki/Context_tree_weighting | reference | science, encyclopedia | 2026-05-05T11:32:09.255560+00:00 | kb-cron |
The context tree weighting method (CTW) is a lossless compression and prediction algorithm by Willems, Shtarkov & Tjalkens 1995. The CTW algorithm is among the very few such algorithms that offer both theoretical guarantees and good practical performance (see, e.g. Begleiter, El-Yaniv & Yona 2004). The CTW algorithm is an “ensemble method”, mixing the predictions of many underlying variable order Markov models, where each such model is constructed using zero-order conditional probability estimators.
== References == Willems; Shtarkov; Tjalkens (1995), "The Context-Tree Weighting Method: Basic Properties", IEEE Transactions on Information Theory, 41 (3), IEEE Transactions on Information Theory: 653–664, Bibcode:1995ITIT...41..653W, doi:10.1109/18.382012 Willems; Shtarkov; Tjalkens (1997), Reflections on "The Context-Tree Weighting Method: Basic Properties", vol. 47, IEEE Information Theory Society Newsletter, CiteSeerX 10.1.1.109.1872{{citation}}: CS1 maint: location missing publisher (link) Begleiter; El-Yaniv; Yona (2004), "On Prediction Using Variable Order Markov Models", Journal of Artificial Intelligence Research, 22, Journal of Artificial Intelligence Research: 385–421, arXiv:1107.0051, doi:10.1613/jair.1491, S2CID 47180476
== External links == Relevant CTW papers and implementations CTW Official Homepage