Acceleration of statistical iterative algorithms for graphical models
| Project/Area Number |
20500263
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | Okayama University of Science |
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Principal Investigator |
KURODA Masahiro 岡山理科大学, 総合情報学部, 准教授 (90279042)
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| Co-Investigator(Kenkyū-buntansha) |
MORI Yuichi 岡山理科大学, 総合情報学部, 教授 (80230085)
SAKAKIHARA Michio 岡山理科大学, 総合情報学部, 教授 (70215614)
NAKAGAWA Shigekazu 倉敷芸術科学大学, 産業科学技術学部, 教授 (90248203)
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| Project Period (FY) |
2008 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2011: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2010: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2009: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2008: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | EMアルゴリズム / グラフィカルモデル / 交互最小二乗法 / マルコフ連鎖モンテカルロ法 / ベクターイプシロン法 / 加速化 / 主成分分析 / 数量化 / 変数選択 / 統計数値計算 / 尺度混在した主成分分析 / 加速化法 / Aitkenδ^2 |
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| Research Abstract |
We developed the acceleration method for the EM algorithm using the vector epsilon algorithm, and then applied it to decomposable log-linear models with missing data. We also proposed MCMC using Markov bases for decomposable log-linear models. Furthermore, we developed a new acceleration method for the Alternating Least Squares(ALS) algorithm using the vector epsilon algorithm, and demonstrated that the acceleration algorithm improves the computational efficiency of the original ALS algorithm.
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Report
(6 results)
Research Products
(52 results)
