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Advances in minimum description length :theory and applications

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A source book for state-of-the-art MDL, including an extensive tutorial and recent theoretical advances and practical applications in fields ranging from bioinformatics to psychology.The process of inductive inference--to infer general laws and principles from particular instances--is the basis of statistical modeling, pattern recognition, and machine learning. The Minimum Descriptive Length (MDL) principle, a powerful method of inductive inference, holds that the best explanation, given a limited set of observed data, is the one that permits the greatest compression of the data--that the more we are able to compress the data, the more we learn about the regularities underlying the data. Advances in Minimum Description Length is a sourcebook that will introduce the scientific community to the foundations of MDL, recent theoretical advances, and practical applications. The book begins with an extensive tutorial on MDL, covering its theoretical underpinnings, practical implications as well as its various interpretations, and its underlying philosophy. The tutorial includes a brief history of MDL--from its roots in the notion of Kolmogorov complexity to the beginning of MDL proper. The book then presents recent theoretical advances, introducing modern MDL methods in a way that is accessible to readers from many different scientific fields. The book concludes with examples of how to apply MDL in research settings that range from bioinformatics and machine learning to psychology.OCLC-licensed vendor bibliographic record.

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Detail Information

Series Title

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Call Number

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Publisher

Cambridge, Mass. : : MIT Press,., 2005.

Collation

1 online resource (x, 444 pages) :illustrations.

Language

English

ISBN/ISSN

9780262274463

Classification

NONE

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

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Subject(s)

Machine learning.
Minimum description length (Information theory)
Information theory.
Mathematical statistics.

Specific Detail Info

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Statement of Responsibility

edited by Peter D. Gr?unwald, In Jae Myung, Mark A. Pitt.

Other Information

Cataloger

dianna Puji

Source

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Validator

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Digital Object Identifier (DOI)

https://direct.mit.edu/books/edited-volume/2553/Advances-in-Minimum-Description-LengthTheory-and

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