On The Relaxation of Orthogonal Tensor Rank and Its Nonconvex Riemannian Optimization for Tensor Completion
Author:
Affiliation:
1. Denso IT Laboratory
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746711.pdf?arnumber=9746711
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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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