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The Resource Advances in minimum description length : theory and applications, edited by Peter D. Grünwald, In Jae Myung, Mark A. Pitt

Advances in minimum description length : theory and applications, edited by Peter D. Grünwald, In Jae Myung, Mark A. Pitt

Label
Advances in minimum description length : theory and applications
Title
Advances in minimum description length
Title remainder
theory and applications
Statement of responsibility
edited by Peter D. Grünwald, In Jae Myung, Mark A. Pitt
Contributor
Subject
Language
eng
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Grünwald, Peter D
  • Myung, In Jae
  • Pitt, Mark A
Series statement
Neural information processing series
http://library.link/vocab/subjectName
  • Minimum description length
  • Statistics
  • Machine learning
  • Information theory
Label
Advances in minimum description length : theory and applications, edited by Peter D. Grünwald, In Jae Myung, Mark A. Pitt
Instantiates
Publication
Bibliography note
Includes bibliographical references and index
Contents
  • Vijay Balasubramanian
  • 4.
  • Hypothesis testing for Poisson vs. geometric distributions using stochastic complexity
  • Aaron D. Lanterman
  • 5.
  • Applications of MDL to selected families of models
  • Andrew J. Hanson and Philip Chi-Wing Fu
  • 6.
  • Algorithmic statistics and Kolmogorov's structure functions
  • Paul Vitanyi
  • 1.
  • 7.
  • Exact minimax predictive density estimation and MDL
  • Feng Liang and Andrew Barron
  • 8.
  • The contribution of parameters to stochastic complexity
  • Dean P. Foster and Robert A. Stine
  • 9.
  • Extended stochastic complexity and its applications to learning
  • Kenji Yamanishi
  • 10.
  • Introducing the minimum description length principle
  • Kolmogorov's structure function in MDL theory and lossy data compression
  • Jorma Rissanen and Ioan Tabus
  • 11.
  • Minimum message length and generalized Bayesian nets with asymmetric languages
  • Joshua W. Comley and David L. Dowe
  • 12.
  • Simultaneous clustering and subset selection via MDL
  • Rebecka Jornsten and Bin Yu
  • 13.
  • An MDL framework for data clustering
  • Peter Grunwald
  • Petri Kontkanen, Petri Myllymaki, Wray Buntine, Jorma Rissanen and Henry Tirri
  • 14.
  • Minimum description length and psychological clustering models
  • Michael D. Lee and Daniel J. Navarro
  • 15.
  • A minimum description length principle for perception
  • Nick Chater
  • 16.
  • Minimum description length and cognitive modeling
  • Yong Su, In Jae Myung and Mark A. Pitt
  • 2.
  • Minimum description length tutorial
  • Peter Grunwald
  • 3.
  • MDL, Bayesian inference, and the geometry of the space of probability distributions
Control code
8667089
Dimensions
27 cm
Extent
x, 444 p.
Isbn
9780262072625
Isbn Type
(alk. paper)
Lccn
2004055932
Other physical details
ill.
System control number
  • (DLC) 2004055932
  • (BNAtoc) 2004055932
Label
Advances in minimum description length : theory and applications, edited by Peter D. Grünwald, In Jae Myung, Mark A. Pitt
Publication
Bibliography note
Includes bibliographical references and index
Contents
  • Vijay Balasubramanian
  • 4.
  • Hypothesis testing for Poisson vs. geometric distributions using stochastic complexity
  • Aaron D. Lanterman
  • 5.
  • Applications of MDL to selected families of models
  • Andrew J. Hanson and Philip Chi-Wing Fu
  • 6.
  • Algorithmic statistics and Kolmogorov's structure functions
  • Paul Vitanyi
  • 1.
  • 7.
  • Exact minimax predictive density estimation and MDL
  • Feng Liang and Andrew Barron
  • 8.
  • The contribution of parameters to stochastic complexity
  • Dean P. Foster and Robert A. Stine
  • 9.
  • Extended stochastic complexity and its applications to learning
  • Kenji Yamanishi
  • 10.
  • Introducing the minimum description length principle
  • Kolmogorov's structure function in MDL theory and lossy data compression
  • Jorma Rissanen and Ioan Tabus
  • 11.
  • Minimum message length and generalized Bayesian nets with asymmetric languages
  • Joshua W. Comley and David L. Dowe
  • 12.
  • Simultaneous clustering and subset selection via MDL
  • Rebecka Jornsten and Bin Yu
  • 13.
  • An MDL framework for data clustering
  • Peter Grunwald
  • Petri Kontkanen, Petri Myllymaki, Wray Buntine, Jorma Rissanen and Henry Tirri
  • 14.
  • Minimum description length and psychological clustering models
  • Michael D. Lee and Daniel J. Navarro
  • 15.
  • A minimum description length principle for perception
  • Nick Chater
  • 16.
  • Minimum description length and cognitive modeling
  • Yong Su, In Jae Myung and Mark A. Pitt
  • 2.
  • Minimum description length tutorial
  • Peter Grunwald
  • 3.
  • MDL, Bayesian inference, and the geometry of the space of probability distributions
Control code
8667089
Dimensions
27 cm
Extent
x, 444 p.
Isbn
9780262072625
Isbn Type
(alk. paper)
Lccn
2004055932
Other physical details
ill.
System control number
  • (DLC) 2004055932
  • (BNAtoc) 2004055932

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      -40.385340 175.617349
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