Artificial Intelligence

Density Ratio Estimation in Machine Learning

Name: Density Ratio Estimation in Machine Learning
Brand: Cambridge University Press
SKU: 9780521190176
Price: 17028.00 INR
Availability: InStock
ISBN: 9780521190176

DENSITY RATIO ESTIMATION IN MA

Contributor(s): Sugiyama, Masashi Author , Suzuki, Taiji Author , Kanamori, Takafumi Author Format: Hardback

Hardback · ISBN 9780521190176

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Key Specifications

ISBN	9780521190176
Subtitle	DENSITY RATIO ESTIMATION IN MA
Publisher	Cambridge University Press
Publication date	May 2012
Language	English
MRP	£135.00 GBP
Page count	342
Item weight	145 g

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods, and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification, and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting, and density ratio fitting as well as describing how these can be applied to machine learning. The book also provides mathematical theories for density ratio estimation including parametric and non-parametric convergence analysis and numerical stability analysis to complete the first and definitive treatment of the entire framework of density ratio estimation in machine learning.

Density Ratio Estimation in Machine Learning

Key Specifications

Sugiyama, Masashi Author

Suzuki, Taiji Author

Kanamori, Takafumi Author

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