| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2011: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2010: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2009: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Research Abstract |
In this work, we theoretically analyzed properties of sampling theories for reproducing kernel Hilbert spaces(RKHS's). Our main contributions are1) we gave a necessary and sufficient condition for a given RKHS and a given set of sampling points to satisfy the sampling theorem, 2) we gave an upper bound of errors in case that the sampling theorem does not hold, and3) we clarified the behavior of the solution in various machine learning problems with respect to sampling points and an adopted RKHS.
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