Batch Processing of Differently Shaped Tensor Data
Project/Area Number |
23700212
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Multi-year Fund |
Research Field |
Perception information processing/Intelligent robotics
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Research Institution | Kyushu University |
Principal Investigator |
INOUE Kohei 九州大学, 芸術工学研究科(研究院), 准教授 (70325570)
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Project Period (FY) |
2011-04-28 – 2015-03-31
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Project Status |
Completed (Fiscal Year 2014)
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Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2014: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2013: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2012: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2011: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
|
Keywords | 画像情報処理 / テンソル / 行列 / 低ランク近似 / 一括処理 / 核ノルム / ベクトル / 次元削減 |
Outline of Final Research Achievements |
For the purpose of the materialization of batch processing of differently shaped tensor data, several methods are proposed in this research includeing symmetric generalized low rank approximation of matrices, a non-iterative approximate solution method for 2DPCA, a dimensionality reduction method for vector data of different dimensions, simultaneous low rank approximation of matrices of different sizes, and simultaneous low rank approximation of matrices by nuclear norm minimization. The effectiveness of the proposed methods was experimentally demonstrated.
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Report
(5 results)
Research Products
(12 results)
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[Presentation] Symmetric GLRAM2012
Author(s)
Kohei Inoue, Kenji Hara, and Kiichi Urahama
Organizer
ICASSP 2012
Place of Presentation
Kyoto International Conference Center
Related Report
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