Partition Tree Weighting

@article{Veness2013PartitionTW,
  title={Partition Tree Weighting},
  author={Joel Veness and Martha White and Michael H. Bowling and Andr{\'a}s Gy{\"o}rgy},
  journal={2013 Data Compression Conference},
  year={2013},
  pages={321-330}
}
This paper introduces the Partition Tree Weighting technique, an efficient meta-algorithm for piecewise stationary sources. The technique works by performing Bayesian model averaging over a large class of possible partitions of the data into locally stationary segments. It uses a prior, closely related to the Context Tree Weighting technique of Willems, that is well suited to data compression applications. Our technique can be applied to any coding distribution at an additional time and space… CONTINUE READING
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Partition Tree Weighting

  • J. Veness, M. White, M. Bowling, A. György
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3 Excerpts

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