Density ratio estimation in machine learning /

"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...

Full description

Bibliographic Details
Main Author:	Sugiyama, Masashi, 1974-
Other Authors:	Suzuki, Taiji, 1981-, Kanamori, Takafumi, 1971-
Format:	Book
Language:	English
Published:	New York : Cambridge University Press, 2012.
Subjects:	Estimation theory. Machine learning. COMPUTERS / Computer Vision & Pattern Recognition.
Online Access:	Cover image

Table of Contents:

Machine generated contents note: Part I. Density Ratio Approach to Machine Learning: 1. Introduction; Part II. Methods of Density Ratio Estimation: 2. Density estimation; 3. Moment matching; 4. Probabilistic classification; 5. Density fitting; 6. Density-ratio fitting; 7. Unified framework; 8. Direct density-ratio estimation with dimensionality reduction; Part III. Applications of Density Ratios in Machine Learning: 9. Importance sampling; 10. Distribution comparison; 11. Mutual information estimation; 12. Conditional probability estimation; Part IV. Theoretical Analysis of Density Ratio Estimation: 13. Parametric convergence analysis; 14. Non-parametric convergence analysis; 15. Parametric two-sample test; 16. Non-parametric numerical stability analysis; Part V. Conclusions: 17. Conclusions and future directions.