2009 Fiscal Year Final Research Report
Applications of Riemannian optimization methods to signal processing
| Project/Area Number |
19700229
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Sensitivity informatics/Soft computing
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| Research Institution | National Institute of Advanced Industrial Science and Technology |
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Principal Investigator |
NISHIMORI Yasunori National Institute of Advanced Industrial Science and Technology, 脳神経情報研究部門, 研究員 (00357724)
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| Project Period (FY) |
2007 – 2009
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| Keywords | 独立成分分析 / ニューラルネットワーク / 信号処理 / 最適化 |
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| Research Abstract |
The set of fixed number of orthogonal subspaces each of which has fixed dimensionality can be regarded as a curved space, termed the flag manifold. Using Riemannian geometry we proposed new optimization methods on this class of manifolds such as Riemannian gradient descent, conjugate gradient method and hybrid MCMC geodesic method. Based on these Riemannian optimization methods new learning algorithms for independent subspace analysis were proposed and their effectiveness over conventional algorithms was experimentally confirmed.
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