Context tree weighting

The context tree weighting method (CTW) is a lossless compression and prediction algorithm by Willems, Shtarkov, and Tjalkens (1995), {{citation}}: Missing or empty |title= (help)CS1 maint: multiple names: authors list (link). 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, and Yona (2004), {{citation}}: Missing or empty |title= (help)CS1 maint: multiple names: authors list (link)).

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.

External links

• Willems, Shtarkov, and Tjalkens (1995), The Context-Tree Weighting Method: Basic Properties, vol. 41, IEEE Transactions on Information Theory{{citation}}: CS1 maint: location missing publisher (link) CS1 maint: multiple names: authors list (link)
• Begleiter, El-Yaniv, and Yona (2004), On Prediction Using Variable Order Markov Models (PDF), vol. 22, Journal of Artificial Intelligence Research, pp. 385–421{{citation}}: CS1 maint: location missing publisher (link) CS1 maint: multiple names: authors list (link)
• Relevant CTW papers and implementations