Tensor ring decomposition represents a powerful technique for understanding high-order tensors. It expresses a tensor as a sum of smaller matrices, effectively simplifying its complexity. This decomposition allows for efficient processing and offers numerous applications across various domains.

Tensor ring decomposition offers a novel approach to data representation by decomposing high-order tensors into a sum of low-rank matrices. This factorization utilizes the inherent structure within data, enabling efficient storage and processing. Applications range from recommender systems to nat