Tensor ring decomposition employs a powerful technique for understanding high-order tensors. It expresses a tensor as a combination of smaller matrices, effectively representing its complexity. This decomposition allows for efficient computation and offers numerous applications across various dom

Tensor rings offer a powerful approach to representing multidimensional data. By decomposing complex tensors into a sum of rank-1 matrices, tensor ring representations capture underlying patterns and structures within the data. This factorization facilitates dimensionality reduction, allowing for

Tensor ring decomposition provides a novel approach to data representation by decomposing high-order tensors into a sum of low-rank matrices. This read more factorization utilizes the inhe