Sparse Sequential Dirichlet Coding

نویسندگان

  • Joel Veness
  • Marcus Hutter
چکیده

This short paper describes a simple coding technique, Sparse Sequential Dirichlet Coding, for multi-alphabet memoryless sources. It is appropriate in situations where only a small, unknown subset of the possible alphabet symbols can be expected to occur in any particular data sequence. We provide a competitive analysis which shows that the performance of Sparse Sequential Dirichlet Coding will be close to that of a Sequential Dirichlet Coder that knows in advance the exact subset of occurring alphabet symbols. Empirically we show that our technique can perform similarly to the more computationally demanding Sequential Sub-Alphabet Estimator, while using less computational resources.

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عنوان ژورنال:
  • CoRR

دوره abs/1206.3618  شماره 

صفحات  -

تاریخ انتشار 2012