Orthogonal random projection for tensor completion
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[1] Bart Vandereycken,et al. Low-rank tensor completion by Riemannian optimization , 2014 .
[2] Christopher J. Hillar,et al. Most Tensor Problems Are NP-Hard , 2009, JACM.
[3] Wei Liu,et al. Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[4] Bin Ran,et al. Tensor completion via a multi-linear low-n-rank factorization model , 2014, Neurocomputing.
[5] Jieping Ye,et al. Tensor Completion for Estimating Missing Values in Visual Data , 2013, IEEE Trans. Pattern Anal. Mach. Intell..
[6] Morten Mørup,et al. Applications of tensor (multiway array) factorizations and decompositions in data mining , 2011, WIREs Data Mining Knowl. Discov..
[7] L. Tucker,et al. Some mathematical notes on three-mode factor analysis , 1966, Psychometrika.
[8] Johan A. K. Suykens,et al. Tensor Versus Matrix Completion: A Comparison With Application to Spectral Data , 2011, IEEE Signal Processing Letters.
[9] J. Chang,et al. Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition , 1970 .
[10] M. Kilmer,et al. Factorization strategies for third-order tensors , 2011 .
[11] B. Recht,et al. Tensor completion and low-n-rank tensor recovery via convex optimization , 2011 .