Mathematical foundation of efficient algorithms for statistical inference
Project/Area Number |
22300098
|
Research Category |
Grant-in-Aid for Scientific Research (B)
|
Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Statistical science
|
Research Institution | The Institute of Statistical Mathematics |
Principal Investigator |
FUKUMIZU Kenji 統計数理研究所, 大学共同利用機関等の部局等, 教授 (60311362)
|
Co-Investigator(Kenkyū-buntansha) |
TANAKA Toshiyuki 京都大学, 情報学研究科, 教授 (10254153)
IKEDA Shiro 統計数理研究所, 数理・推論研究系, 准教授 (30336101)
KABASHIMA Yoshiyuki 東京工業大学, 総合理工学研究科, 教授 (80260652)
|
Project Period (FY) |
2010-04-01 – 2014-03-31
|
Project Status |
Completed (Fiscal Year 2013)
|
Budget Amount *help |
¥12,220,000 (Direct Cost: ¥9,400,000、Indirect Cost: ¥2,820,000)
Fiscal Year 2013: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2012: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2011: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2010: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
|
Keywords | グラフ / アルゴリズム / 確率計算 / 情報幾何 / 位相幾何 |
Research Abstract |
As a new mathematical method for analyzing propagation algorithms on graphs, a novel Graph zeta function has been proposed for the analysis of the loopy belief propagation algorithm, and used for revealing stronger theoretical results than the known ones. Also, a method of loop expansion has been proposed for analyzing the approximation error of the loopy belief propagation. As a mathematical foundation of the expectation propagation, an infinite dimensional exponential family has been proposed based on positive definite kernels, and its estimation methods and theoretical properties have been studied.
|
Report
(5 results)
Research Products
(70 results)
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
[Journal Article] Kernel Bayes' Rule2011
Author(s)
Fukumizu, K., Song, L., Gretton, A.
-
Journal Title
Advances in Neural Information Processing Systems
Volume: 24
Pages: 1737-1745
Related Report
Peer Reviewed
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-