Abstract:
This work was inspired by the paper of Vereshchagin and Vitanyi, where Kolmogorov's unpublished work on his structure function and the associated minimal sufficient stati...Show MoreMetadata
Abstract:
This work was inspired by the paper of Vereshchagin and Vitanyi, where Kolmogorov's unpublished work on his structure function and the associated minimal sufficient statistics decomposition in the algorithmic theory of information is studied. The extension of Kolmogorov's great ideas to probability model classes turns out to add a new chapter to the MDL theory, which also provides an alternative approach to Shannon's rate-distortion theory.
Published in: Proceedings of the IEEE Information Theory Workshop
Date of Conference: 25-25 October 2002
Date Added to IEEE Xplore: 06 January 2003
Print ISBN:0-7803-7629-3