| Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2015: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2014: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Outline of Final Research Achievements |
In this research project, we aim to pioneer new statistical theories for big data, ahead of the world. We have developed new theories and methodologies in latent structural analysis for big data: irregular and non-Gaussian data contaminated with outliers and missing values. New theories and methodologies guarantee stable and high accuracy at low computational cost. The findings of this research project are as follows: (1) Developments of the irregular inference theory for big data with diversity. (2) Developments of high-speed and highly accurate latent structural analysis for big data. (3) Pioneering latent structural analysis robust against outliers and missing values.
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