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Tensor completion estimates missing components by exploiting the low-rank structure of multi-way data.
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2012
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2013
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2013
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2013
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2014
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H. Tan, B. Cheng, W. Wang, Y.-J. Zhang, and B. Ran, “Tensor completion via a multi-linear low-n-rank factorization model,” Neurocomputing
2014
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F. Zhu, Y. Wang, B. Fan, S. Xiang, G. Meng, and C. Pan, “Spectral unmixing via data-guided sparsity,” IEEE Transactions on Image Processing
2014
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2014
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2015
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N. D. Sidiropoulos, L. De Lathauwer, X. Fu, K. Huang, E. E. Papalexakis, and C. Faloutsos, “Tensor decomposition for signal processing and machine learning,” IEEE Transactions on Signal Processing
2017
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J. A. Bengua, H. N. Phien, H. D. Tuan, and M. N. Do, “Efficient tensor completion for color image and video recovery: low-rank tensor train,” IEEE Transactions on Image Processing
2017
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2017
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2015
Cited alongside, same era.
Y. Liu, F. Shang, L. Jiao, J. Cheng, and H. Cheng, “Trace norm regularized CANDECOMP/PARAFAC decomposition with missing data,” IEEE Transactions on Cybernetics
2015
Cited alongside, same era.
Q. Zhao, L. Zhang, and A. Cichocki, “Bayesian CP factorization of incomplete tensors with automatic rank determination,” IEEE Transactions on Pattern Analysis and Machine Intelligence
2015
Cited alongside, same era.
Y. Xu, R. Hao, W. Yin, and Z. Su, “Parallel matrix factorization for low-rank tensor completion,” Inverse Problems and Imaging
2015
Cited alongside, same era.
B. Du, M. Zhang, L. Zhang, R. Hu, and D. Tao, “Pltd: Patch-based low-rank tensor decomposition for hyperspectral images,” IEEE Transactions on Multimedia
2016
Cited alongside, same era.
H. Kasai, “Online low-rank tensor subspace tracking from incomplete data by cp decomposition using recursive least squares,” in 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
2016
Cited alongside, same era.
A. Cichocki, N. Lee, I. Oseledets, A.-H. Phan, Q. Zhao, D. P. Mandic, et al
2016
Cited alongside, same era.
Y. Liu, F. Shang, W. Fan, J. Cheng, and H. Cheng, “Generalized higher order orthogonal iteration for tensor learning and decomposition,” IEEE Transactions on Neural Networks and Learning Systems
2016
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2017
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B. Xiong, Q. Liu, J. Xiong, S. Li, S. Wang, and D. Liang, “Field-of-experts filters guided tensor completion,” IEEE Transactions on Multimedia
2018
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K. Ye and L.-H. Lim, “Tensor network ranks,” arXiv preprint arXiv:1801.02662
2018
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Z. Long, Y. Liu, L. Chen, and C. Zhu, “Low rank tensor completion for multiway visual data,” Signal Processing
2019
Closest in time.
W. He, L. Yuan, and N. Yokoya, “Total-variation-regularized tensor ring completion for remote sensing image reconstruction,” in ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
2019
Closest in time.
M. Zhou, Y. Liu, Z. Long, L. Chen, and C. Zhu, “Tensor rank learning in CP decomposition via convolutional neural network,” Signal Processing: Image Communication
2019
Closest in time.
Y. Liu, Z. Long, H. Huang, and C. Zhu, “Low cp rank and tucker rank tensor completion for estimating missing components in image data,” IEEE Transactions on Circuits and Systems for Video Technology
2019
Closest in time.
Q. Zhao, M. Sugiyama, L. Yuan, and A. Cichocki, “Learning efficient tensor representations with ring-structured networks,” in ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
2019
Closest in time.