| Project/Area Number |
24700154
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Intelligent informatics
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| Research Institution | Institute of Physical and Chemical Research |
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Principal Investigator |
ZHAO QIBIN 独立行政法人理化学研究所, 脳科学総合研究センター, 研究員 (30599618)
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| Project Period (FY) |
2012-04-01 – 2014-03-31
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2013: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2012: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
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| Keywords | Machine learning / Tensor analysis / Kernel machines / Brain computer interface / Brain signal processing / Bayesian inference / EEG Hyperscanning |
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| Research Abstract |
This project focuses on two aspects: 1) Multiway data (tensor) analysis methods. We proposed and developed many supervised learning methods for tensor data, which can perform multilinear regression or classification on multi-dimensional structured data. In addition, in order to capture the nonlinear relations of tensor data, we proposed a family of kernel functions that can handle tensor-valued inputs, which opens a door for applying kernel machines to tensor space. 2) Brain computer interface and brain signal analysis. We developed an affective brain computer interface (BCI) using emotional faces as stimuli. On the other hand, we extensively applied our proposed tensor techniques for analyzing brain signals, which have shown significant improvement of performance in terms of decoding of brain signals, feature extractions and classifications of ERPs.
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