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Context tree weighting

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Title: Context tree weighting  
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Subject: Lossless compression, Shannon–Fano–Elias coding, Elias gamma coding, Dynamic Markov compression, Prediction by partial matching
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Context tree weighting

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 41, IEEE Transactions on Information Theory 
  • Begleiter; El-Yaniv; Yona (2004), On Prediction Using Variable Order Markov Models 22, Journal of Artificial Intelligence Research:  

External links

  • Relevant CTW papers and implementations
  • CTW Official Homepage


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