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Learning With The Minimum Description Length Principle 1st Edition Kenji Yamanishi

Name: Learning With The Minimum Description Length Principle 1st Edition Kenji Yamanishi
SKU: BELL-52357218
Price: 31.00 USD
Availability: InStock
Rating: 5 (20 reviews)

SKU: BELL-52357218

$ 31.00 ~~$ 45.00~~ (-31%)

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Learning With The Minimum Description Length Principle 1st Edition Kenji Yamanishi instant download after payment.

Publisher: Springer

File Extension: PDF

File size: 5.14 MB

Pages: 359

Author: Kenji Yamanishi

ISBN: 9789819917891, 9789819917907, 9819917891, 9819917905

Language: English

Year: 2023

Edition: 1

Product desciption

Learning With The Minimum Description Length Principle 1st Edition Kenji Yamanishi by Kenji Yamanishi 9789819917891, 9789819917907, 9819917891, 9819917905 instant download after payment.

This book introduces readers to the minimum description length (MDL) principle and its applications in learning. The MDL is a fundamental principle for inductive inference, which is used in many applications including statistical modeling, pattern recognition and machine learning. At its core, the MDL is based on the premise that “the shortest code length leads to the best strategy for learning anything from data.” The MDL provides a broad and unifying view of statistical inferences such as estimation, prediction and testing and, of course, machine learning.

The content covers the theoretical foundations of the MDL and broad practical areas such as detecting changes and anomalies, problems involving latent variable models, and high dimensional statistical inference, among others. The book offers an easy-to-follow guide to the MDL principle, together with other information criteria, explaining the differences between their standpoints.

Written in a systematic, concise and comprehensive style, this book is suitable for researchers and graduate students of machine learning, statistics, information theory and computer science.