Missing Data Recovery Based on Tensor-CUR Decomposition
Tensor completion is a higher way analog of matrix completion, which has proven to be a powerful tool for data analysis. In this paper, we formulate the missing data recovery problem of a three-way tensor as a tensor completion problem. We propose a novel tensor completion method based on tensor-CUR...
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| Format: | Article |
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IEEE
2018-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8096992/ |
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doaj-364bd702e65b445db45705f85f21484e2021-03-29T20:32:40ZengIEEEIEEE Access2169-35362018-01-01653254410.1109/ACCESS.2017.27701468096992Missing Data Recovery Based on Tensor-CUR DecompositionLele Wang0https://orcid.org/0000-0003-1011-4856Kun Xie1Thabo Semong2Huibin Zhou3College of Computer Science and Electronics Engineering, Hunan University, Changsha, ChinaCollege of Computer Science and Electronics Engineering, Hunan University, Changsha, ChinaCollege of Computer Science and Electronics Engineering, Hunan University, Changsha, ChinaCollege of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha, ChinaTensor completion is a higher way analog of matrix completion, which has proven to be a powerful tool for data analysis. In this paper, we formulate the missing data recovery problem of a three-way tensor as a tensor completion problem. We propose a novel tensor completion method based on tensor-CUR decomposition to estimate the missing data from limited samples. Computational experiments demonstrate that the proposed method yields a superior performance over other existing approaches.https://ieeexplore.ieee.org/document/8096992/Data recoverytensor completiontensor-CUR decomposition |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Lele Wang Kun Xie Thabo Semong Huibin Zhou |
| spellingShingle |
Lele Wang Kun Xie Thabo Semong Huibin Zhou Missing Data Recovery Based on Tensor-CUR Decomposition IEEE Access Data recovery tensor completion tensor-CUR decomposition |
| author_facet |
Lele Wang Kun Xie Thabo Semong Huibin Zhou |
| author_sort |
Lele Wang |
| title |
Missing Data Recovery Based on Tensor-CUR Decomposition |
| title_short |
Missing Data Recovery Based on Tensor-CUR Decomposition |
| title_full |
Missing Data Recovery Based on Tensor-CUR Decomposition |
| title_fullStr |
Missing Data Recovery Based on Tensor-CUR Decomposition |
| title_full_unstemmed |
Missing Data Recovery Based on Tensor-CUR Decomposition |
| title_sort |
missing data recovery based on tensor-cur decomposition |
| publisher |
IEEE |
| series |
IEEE Access |
| issn |
2169-3536 |
| publishDate |
2018-01-01 |
| description |
Tensor completion is a higher way analog of matrix completion, which has proven to be a powerful tool for data analysis. In this paper, we formulate the missing data recovery problem of a three-way tensor as a tensor completion problem. We propose a novel tensor completion method based on tensor-CUR decomposition to estimate the missing data from limited samples. Computational experiments demonstrate that the proposed method yields a superior performance over other existing approaches. |
| topic |
Data recovery tensor completion tensor-CUR decomposition |
| url |
https://ieeexplore.ieee.org/document/8096992/ |
| work_keys_str_mv |
AT lelewang missingdatarecoverybasedontensorcurdecomposition AT kunxie missingdatarecoverybasedontensorcurdecomposition AT thabosemong missingdatarecoverybasedontensorcurdecomposition AT huibinzhou missingdatarecoverybasedontensorcurdecomposition |
| _version_ |
1724194550759555072 |