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- 2011051726 contributor B12160640.
- 2011051726 contributor B12160641.
- 2011051726 created "2012.".
- 2011051726 date "2012".
- 2011051726 date "2012.".
- 2011051726 dateCopyrighted "2012.".
- 2011051726 description "Includes bibliographical references (p. 309-325) and index.".
- 2011051726 description "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.".
- 2011051726 extent "xii, 329 p. :".
- 2011051726 identifier "0521190177 (hardback)".
- 2011051726 identifier "9780521190176 (hardback)".
- 2011051726 identifier 9780521190176.jpg.
- 2011051726 issued "2012".
- 2011051726 issued "2012.".
- 2011051726 language "eng".
- 2011051726 publisher "New York : Cambridge University Press,".
- 2011051726 subject "006.3/1 23".
- 2011051726 subject "Estimation theory.".
- 2011051726 subject "Machine learning.".
- 2011051726 subject "QA276.8 .S84 2012".
- 2011051726 tableOfContents "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.".
- 2011051726 title "Density ratio estimation in machine learning / Masashi Sugiyama, Taiji Suzuki, Takafumi Kanamori.".
- 2011051726 type "text".
