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Advances in Minimum Description Length Theory and Applications

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ISBN-10: 0262072629

ISBN-13: 9780262072625

Edition: 2005

Authors: Peter D. Gr�nwald, In Jae Myung, Mark A. Pitt

List price: $11.75
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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 Lengthis a sourcebook that will introduce the scientific community to the foundations of MDL, recent theoretical advances, and practical…    
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Book details

List price: $11.75
Copyright year: 2005
Publisher: MIT Press
Publication date: 2/25/2005
Binding: Hardcover
Pages: 372
Size: 8.25" wide x 10.25" long x 1.25" tall
Weight: 2.442
Language: English

Series Foreword
Introductory Chapters
Introducing the Minimum Description Length Principle
Minimum Description Length Tutorial
MDL, Bayesian Inference, and the Geometry of the Space of Probability Distributions
Hypothesis Testing for Poisson vs. Geometric Distributions Using Stochastic Complexity
Applications of MDL to Selected Families of Models
Algorithmic Statistics and Kolmogorov's Structure Functions
Theoretical Advances
Exact Minimax Predictive Density Estimation and MDL
The Contribution of Parameters to Stochastic Complexity
Extended Stochastic Complexity and Its Applications to Learning
Kolmogorov's Structure Function in MDL Theory and Lossy Data Compression
Practical Applications
Minimum Message Length and Generalized Bayesian Nets with Asymmetric Languages
Simultaneous Clustering and Subset Selection via MDL
An MDL Framework for Data Clustering
Minimum Description Length and Psychological Clustering Models
A Minimum Description Length Principle for Perception
Minimum Description Length and Cognitive Modeling