Learning with the Minimum Description Length Principle
Author:   Kenji Yamanishi
Publisher:   Springer Verlag, Singapore
Edition:   2023 ed.
ISBN:  

9789819917921


Pages:   339
Publication Date:   16 September 2024
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Learning with the Minimum Description Length Principle


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Author:   Kenji Yamanishi
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Verlag, Singapore
Edition:   2023 ed.
ISBN:  

9789819917921


ISBN 10:   9819917921
Pages:   339
Publication Date:   16 September 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Information and Coding.- Parameter Estimation.- Model Selection.- Latent Variable Model Selection.- Sequential Prediction.- MDL Change Detection.- Continuous Model Selection.- Extension of Stochastic Complexity.- Mathematical Preliminaries.

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Author Information

Kenji Yamanishi is a Professor at the Graduate School of Information Science and Technology, University of Tokyo, Japan. After completing the master course at the Graduate School of University of Tokyo, he joined NEC Corporation in 1987. He received his doctorate (in Engineering) from the University of Tokyo in 1992 and joined the University faculty in 2009. His research interests and contributions are in the theory of the minimum description length principle, information-theoretic learning theory, and data science applications such as anomaly detection and text mining.

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