Sumio Watanabe (渡辺 澄夫, Watanabe Sumio, born 1959) is a Japanese mathematician and engineer working in probability theory, applied algebraic geometry and Bayesian statistics. He is currently[when?] a professor at Tokyo Institute of Technology in the Department of Computational Intelligence and Systems Science.[1] He is the author of the text, Algebraic Geometry and Statistical Learning Theory, which proposes a generalization of Fisher's regular statistical theory to singular statistical models.[2]
Sumio Watanabe | |
|---|---|
| Born | 31 March 1959 |
| Nationality |  Japan |
| Alma mater | Kyoto University (M.S., 1984) Tokyo Institute of Technology (Ph.D., 1993) |
| Known for | Watanabe-Akaike information criterion singular statistical models |
| Awards | Ichimura Prize for Science (2006)[3] |
| Scientific career | |
| Fields | Mathematics |
| Institutions | Tokyo Institute of Technology Gifu University |
Books
edit- Mathematical Theory of Bayesian Statistics, CRC Press, 2018, ISBN 9781482238068
- Algebraic Geometry and Statistical Learning Theory, Cambridge University Press, 2009.
References
edit- ^ Watanabe, Sumio. "CV". Retrieved 15 June 2018.
- ^ N. Loménie. "IAPR Newsletter: Review of Algebraic Geometry and Statistical Learning Theory". Retrieved 15 June 2018.
- ^ Ichimura Foundation for New Technology. "38th Past Awards List / Ichimura Prize Presentation".
External links
edit- Algebraic Geometrical Method in Singular Statistical Estimation. Presentation at Algebraic Statistics Seminar, MSRI, December 17, 2008 (video)
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