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Found 3 papers, 1 papers with code
Structured model selection via $\ell_1-\ell_2$ optimization
Automated model selection is an important application in science and engineering.
"Sparse + Low-Rank'' Tensor Completion Approach for Recovering Images and Videos
By the multi-dimensional nature of color images and videos, in this paper, we propose a novel tensor completion approach, which is able to efficiently explore the sparsity of tensor data under the discrete cosine transform (DCT).
Low-Rank and Sparse Enhanced Tucker Decomposition for Tensor Completion
Our model possesses a sparse regularization term to promote a sparse core tensor of the Tucker decomposition, which is beneficial for tensor data compression.
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