Tensor-Tensor Product Toolbox
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Abstract (arXiv)
The tensor-tensor product (t-product) [M. E. Kilmer and C. D. Martin, 2011] is a natural generalization of matrix multiplication. Based on t-product, many operations on matrix can be extended to tensor cases, including tensor SVD, tensor spectral norm, tensor nuclear norm [C. Lu, et al., 2018] and many others. The linear algebraic structure of tensors are similar to the matrix cases. We develop a Matlab toolbox to implement several basic operations on tensors based on t-product. The toolbox is available at https://github.com/canyilu/tproduct.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Jun 2018.
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Citing papers per year: 2023: 1; 2024: 1; 2025: 2.
4 papers.
- 2023Efficiency of First-Order Methods for Low-Rank Tensor Recovery with the Tensor Nuclear Norm Under Strict Complementaritycited by 1
- 2024Power of ℓ1-Norm Regularized Kaczmarz Algorithms for High-Order Tensor Recoverycited by 1
- 2025Quantile-Based Randomized Kaczmarz for Corrupted Tensor Linear Systemscited by 0
- 2025Tensor Dynamic Mode Decompositioncited by 0
- 2025Tensor Dynamic Mode Decomposition4 Aug 2025
- 2025Quantile-Based Randomized Kaczmarz for Corrupted Tensor Linear Systems23 Mar 2025
- 2024Power of ℓ1-Norm Regularized Kaczmarz Algorithms for High-Order Tensor Recovery14 May 2024
- 2023Efficiency of First-Order Methods for Low-Rank Tensor Recovery with the Tensor Nuclear Norm Under Strict Complementarity3 Aug 2023