On The Relaxation of Orthogonal Tensor Rank and Its Nonconvex Riemannian Optimization for Tensor Completion

Author:

Ozawa Keisuke1

Affiliation:

1. Denso IT Laboratory

Publisher

IEEE

Reference24 articles.

1. A third-order generalization of the matrix svd as a product of third-order tensors;kilmer;Tech Report Technical Report TR-2008-4 Tufts University Department of Computer Science,2008

2. Novel Methods for Multilinear Data Completion and De-noising Based on Tensor-SVD

3. Low-Rank Tensor Completion With a New Tensor Nuclear Norm Induced by Invertible Linear Transforms

4. Dictionary learning with low-rank coding coefficients for tensor completion;jiang,2020

5. Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Łojasiewicz Inequality

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