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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Sugiyama, Masashi, 1974-
Otros Autores: Suzuki, Taiji, 1981-, Kanamori, Takafumi, 1972-
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York : Cambridge University Press, 2012.
Temas:
Estimation theory.
Machine learning.
Théorie de l'estimation.
Apprentissage automatique.
COMPUTERS > Computer Vision & Pattern Recognition.
COMPUTERS > Enterprise Applications > Business Intelligence Tools.
COMPUTERS > Intelligence (AI) & Semantics.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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.

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