GMNS-based tensor decomposition
In this thesis, we focus on the divide-and-conquer approach for PARAFAC and highorder singular value decomposition (HOSVD) of three-way tensors. HOSVD is a specific orthogonal form of Tucker decomposition. Recently, generalized minimum noise subspace (GMNS) was proposed by Nguyen et al. in as a good...
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| 機構: | Vietnam National University, Hanoi |
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oai:112.137.131.14:VNU_123-698922020-02-21T04:30:14Z GMNS-based tensor decomposition Lê, Trung Thành Nguyễn, Linh Trung ĐHQGHN - Trường Đại học Công nghệ Kỹ thuật ; Viễn thông 621.382 In this thesis, we focus on the divide-and-conquer approach for PARAFAC and highorder singular value decomposition (HOSVD) of three-way tensors. HOSVD is a specific orthogonal form of Tucker decomposition. Recently, generalized minimum noise subspace (GMNS) was proposed by Nguyen et al. in as a good technique for subspace analysis. This method is highly beneficial in practice because it not only substantially reduces the computational complexity in finding bases for these subspaces, but also provides high estimation accuracy. This motivates us to propose in this thesis new implementations for tensor decomposition based on GMNS Luận văn chuyên ngành kỹ thuật viễn thông 2020-02-15T07:10:27Z 2020-02-15T07:10:27Z 2018 Theses GMNS-based tensor decomposition 60520208 http://repository.vnu.edu.vn/handle/VNU_123/69892 LE-T en 68 p. application/pdf |
| institution |
Vietnam National University, Hanoi |
| building |
VNU Library & Information Center |
| country |
Vietnam |
| collection |
VNU Digital Repository |
| language |
English |
| topic |
Kỹ thuật ; Viễn thông 621.382 |
| spellingShingle |
Kỹ thuật ; Viễn thông 621.382 Lê, Trung Thành GMNS-based tensor decomposition |
| description |
In this thesis, we focus on the divide-and-conquer approach for PARAFAC and highorder singular value decomposition (HOSVD) of three-way tensors. HOSVD is a specific orthogonal form of Tucker decomposition. Recently, generalized minimum noise subspace (GMNS) was proposed by Nguyen et al. in as a good technique for subspace analysis. This method is highly beneficial in practice because it not only substantially reduces the computational complexity in finding bases for these subspaces, but also provides high estimation accuracy. This motivates us to propose in this thesis new implementations for tensor decomposition based on GMNS |
| author2 |
Nguyễn, Linh Trung |
| author_facet |
Nguyễn, Linh Trung Lê, Trung Thành |
| format |
Theses |
| author |
Lê, Trung Thành |
| author_sort |
Lê, Trung Thành |
| title |
GMNS-based tensor decomposition |
| title_short |
GMNS-based tensor decomposition |
| title_full |
GMNS-based tensor decomposition |
| title_fullStr |
GMNS-based tensor decomposition |
| title_full_unstemmed |
GMNS-based tensor decomposition |
| title_sort |
gmns-based tensor decomposition |
| publishDate |
2020 |
| url |
http://repository.vnu.edu.vn/handle/VNU_123/69892 |
| _version_ |
1680964822560145408 |