Verfügbarkeit: The minimum description length principle /

The minimum description length principle /:

A comprehensive introduction and reference guide to the minimum description length (MDL) Principle that is accessible to researchers dealing with inductive reference in diverse areas including statistics, pattern classification, machine learning, data min.

Gespeichert in:

Bibliographische Detailangaben
1. Verfasser:	Grünwald, Peter D.
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Cambridge, Mass. : MIT Press, ©2007.
Schriftenreihe:	Adaptive computation and machine learning.
Schlagworte:	Minimum description length (Information theory) Longueur de description minimale (Théorie de l'information) COMPUTERS > Information Theory. COMPUTER SCIENCE/Machine Learning & Neural Networks
Online-Zugang:	Volltext
Zusammenfassung:	A comprehensive introduction and reference guide to the minimum description length (MDL) Principle that is accessible to researchers dealing with inductive reference in diverse areas including statistics, pattern classification, machine learning, data min.
Beschreibung:	1 online resource (xxxii, 703 pages) : illustrations
Bibliographie:	Includes bibliographical references (pages 651-673) and indexes.
ISBN:	9780262256292 0262256290 1282096354 9781282096356 9781429465601 1429465603

Internformat

MARC


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contents	List of Figures; Series Foreword; Foreword; Preface; PART I -- Introductory Material; 1 -- Learning, Regularity, and Compression; 2 -- Probabilistic and Statistical Preliminaries; 3 -- Information-Theoretic Preliminaries; 4 -- Information-Theoretic Properties of Statistical Models; 5 -- Crude Two-Part Code MDL; PART II -- Universal Coding; 6 -- Universal Coding with Countable Models; 7 -- Parametric Models: Normalized Maximum Likelihood; 8 -- Parametric Models: Bayes; 9 -- Parametric Models: Prequential Plug-in; 10 -- Parametric Models: Two-Part; 11 -- NMLWith Innite Complexity. 12 -- Linear RegressionPART III -- Refined MDL; 14 -- MDL Model Selection; 15 -- MDL Prediction and Estimation; 16 -- MDL Consistency and Convergence; 17 -- MDL in Context; PART IV -- Additional Background; 18 -- The Exponential or "Maximum Entropy" Families; 19 -- Information-Theoretic Properties of Exponential Families; References; List of Symbols; Subject Index.
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owner	MAIN DE-863 DE-BY-FWS
owner_facet	MAIN DE-863 DE-BY-FWS
physical	1 online resource (xxxii, 703 pages) : illustrations
psigel	ZDB-4-EBA
publishDate	2007
publishDateSearch	2007
publishDateSort	2007
publisher	MIT Press,
record_format	marc
series	Adaptive computation and machine learning.
series2	Adaptive computation and machine learning
spelling	Grünwald, Peter D. The minimum description length principle / Peter D. Grünwald. Cambridge, Mass. : MIT Press, ©2007. 1 online resource (xxxii, 703 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier data file Adaptive computation and machine learning Includes bibliographical references (pages 651-673) and indexes. Print version record. A comprehensive introduction and reference guide to the minimum description length (MDL) Principle that is accessible to researchers dealing with inductive reference in diverse areas including statistics, pattern classification, machine learning, data min. List of Figures; Series Foreword; Foreword; Preface; PART I -- Introductory Material; 1 -- Learning, Regularity, and Compression; 2 -- Probabilistic and Statistical Preliminaries; 3 -- Information-Theoretic Preliminaries; 4 -- Information-Theoretic Properties of Statistical Models; 5 -- Crude Two-Part Code MDL; PART II -- Universal Coding; 6 -- Universal Coding with Countable Models; 7 -- Parametric Models: Normalized Maximum Likelihood; 8 -- Parametric Models: Bayes; 9 -- Parametric Models: Prequential Plug-in; 10 -- Parametric Models: Two-Part; 11 -- NMLWith Innite Complexity. 12 -- Linear RegressionPART III -- Refined MDL; 14 -- MDL Model Selection; 15 -- MDL Prediction and Estimation; 16 -- MDL Consistency and Convergence; 17 -- MDL in Context; PART IV -- Additional Background; 18 -- The Exponential or "Maximum Entropy" Families; 19 -- Information-Theoretic Properties of Exponential Families; References; List of Symbols; Subject Index. Minimum description length (Information theory) http://id.loc.gov/authorities/subjects/sh2005005359 Longueur de description minimale (Théorie de l'information) COMPUTERS Information Theory. bisacsh Minimum description length (Information theory) fast COMPUTER SCIENCE/Machine Learning & Neural Networks has work: The minimum description length principle (Text) https://id.oclc.org/worldcat/entity/E39PCH7mjfxGWcbDJQtDVY9cmq https://id.oclc.org/worldcat/ontology/hasWork Print version: Grünwald, Peter D. Minimum description length principle. Cambridge, Mass. : MIT Press, ©2007 0262072815 9780262072816 (DLC) 2006046646 (OCoLC)70292149 Adaptive computation and machine learning. http://id.loc.gov/authorities/names/n97066095 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=189263 Volltext
spellingShingle	Grünwald, Peter D. The minimum description length principle / Adaptive computation and machine learning. List of Figures; Series Foreword; Foreword; Preface; PART I -- Introductory Material; 1 -- Learning, Regularity, and Compression; 2 -- Probabilistic and Statistical Preliminaries; 3 -- Information-Theoretic Preliminaries; 4 -- Information-Theoretic Properties of Statistical Models; 5 -- Crude Two-Part Code MDL; PART II -- Universal Coding; 6 -- Universal Coding with Countable Models; 7 -- Parametric Models: Normalized Maximum Likelihood; 8 -- Parametric Models: Bayes; 9 -- Parametric Models: Prequential Plug-in; 10 -- Parametric Models: Two-Part; 11 -- NMLWith Innite Complexity. 12 -- Linear RegressionPART III -- Refined MDL; 14 -- MDL Model Selection; 15 -- MDL Prediction and Estimation; 16 -- MDL Consistency and Convergence; 17 -- MDL in Context; PART IV -- Additional Background; 18 -- The Exponential or "Maximum Entropy" Families; 19 -- Information-Theoretic Properties of Exponential Families; References; List of Symbols; Subject Index. Minimum description length (Information theory) http://id.loc.gov/authorities/subjects/sh2005005359 Longueur de description minimale (Théorie de l'information) COMPUTERS Information Theory. bisacsh Minimum description length (Information theory) fast
subject_GND	http://id.loc.gov/authorities/subjects/sh2005005359
title	The minimum description length principle /
title_auth	The minimum description length principle /
title_exact_search	The minimum description length principle /
title_full	The minimum description length principle / Peter D. Grünwald.
title_fullStr	The minimum description length principle / Peter D. Grünwald.
title_full_unstemmed	The minimum description length principle / Peter D. Grünwald.
title_short	The minimum description length principle /
title_sort	minimum description length principle
topic	Minimum description length (Information theory) http://id.loc.gov/authorities/subjects/sh2005005359 Longueur de description minimale (Théorie de l'information) COMPUTERS Information Theory. bisacsh Minimum description length (Information theory) fast
topic_facet	Minimum description length (Information theory) Longueur de description minimale (Théorie de l'information) COMPUTERS Information Theory.
url	https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=189263
work_keys_str_mv	AT grunwaldpeterd theminimumdescriptionlengthprinciple AT grunwaldpeterd minimumdescriptionlengthprinciple

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