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doi.org/10.1016/j.amc.2019.124783
Low-rank tensor train for tensor robust principal component analysis
Jing‐Hua Yang
10
,
Xi-Le Zhao
46
,
...,
Ting‐Zhu Huang
53
View all 5 authors
Applied Mathematics and Computation
3.40
Volume: 367, Pages: 124783 - 124783
Published
: Oct 4, 2019
107
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Basic Info
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Citations
Paper Fields
Combinatorics
Pattern recognition (psychology)
Tensor (intrinsic definition)
Symmetric tensor
Mathematics
Noise (video)
Algorithm
Image (mathematics)
Mathematical optimization
Tensor density
Rank (graph theory)
Mathematical analysis
Artificial intelligence
Tensor field
Principal component analysis
Geometry
Robust principal component analysis
Computer science
Exact solutions in general relativity
Applied mathematics
Paper Details
Title
Low-rank tensor train for tensor robust principal component analysis
DOI
doi.org/10.1016/j.amc.2019.124783
Published Date
Oct 4, 2019
Journal
Applied Mathematics and Computation
Volume
367
Pages
124783 - 124783
Notes
History
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