この論文をさがす
抄録
Contrasting "geometric fitting", for which the noise level is taken as the asymptotic variable, with "statistical inference", for which the number of observations is taken as the asymptotic variable, we give a new definition of the "geometric AIC" and the "geometric MDL" as the counterparts of Akaike's AIC and Rissanen's MDL. We discuss various theoretical and practical problems that emerge from our analysis. Finally, we show, doing experiments using synthetic and real images, that the geometric MDL does not necessarily outperform the geometric AIC and that the two criteria have very different characteristics.
収録刊行物
-
- Memoirs of the Faculty of Engineering, Okayama University
-
Memoirs of the Faculty of Engineering, Okayama University 36 (1), 59-77, 2001-12
Faculty of Engineering, Okayama University
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1390290699799540992
-
- NII論文ID
- 80012855281
-
- NII書誌ID
- AA10699856
-
- ISSN
- 04750071
-
- DOI
- 10.18926/47001
-
- 本文言語コード
- en
-
- データソース種別
-
- JaLC
- IRDB
- CiNii Articles