Mar 15, 2024 · Abstract. In this paper, we introduce a unified low-rank and sparse enhanced Tucker decomposition model for tensor completion. Our model ...
Oct 1, 2020 · In this paper, we introduce a unified low-rank and sparse enhanced Tucker decomposition model for tensor completion.
Feb 27, 2024 · AbstractIn this paper, we introduce a unified low-rank and sparse enhanced Tucker decomposition model for tensor completion.
In this paper, we introduce a unified low-rank and sparse enhanced Tucker decomposition model for tensor completion. Our model possesses a sparse ...
This paper shall incorporate the low-rank and sparse regularization technique to enhance Tucker decomposition for tensor completion and show that this model ...
This paper proposes a novel Tucker-based model to consider global and local information in imaging. Specifically, the weighted factor matrix rank and core ...
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Abstract:Tensor completion refers to the task of estimating the missing data from an incomplete measurement or observation, which is a core problem ...
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Dec 15, 2023 · This paper proposes a novel Tucker-based model to consider global and local information in imaging. Specifically, the weighted factor matrix ...
This paper studies a tensor-structured linear regression model with a scalar response variable and tensor-structured predictors.
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Jun 19, 2024 · A low-rank and sparse enhanced Tucker decomposition approach for tensor completion. ... Enhanced Tucker Decomposition for Tensor Completion ...