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, IEEE Transactions on Information Theory, 41 (3): 653–664, 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, CiteSeerX10.1.1.109.1872{{citation}}: CS1 maint: location missing publisher (link)
Begleiter; El-Yaniv; Yona (2004), "On Prediction Using Variable Order Markov Models", Journal of Artificial Intelligence Research, Journal of Artificial Intelligence Research, 22: 385–421, arXiv:1107.0051, doi:10.1613/jair.1491, S2CID 47180476
External links
Relevant CTW papers and implementations
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