Tensor ring decomposition represents a powerful technique for understanding high-order tensors. It expresses a tensor as a sum of smaller matrices, effectively reducing its complexity. This decomposition allows for efficient computation and offers numerous utilization across various domains. … Read More

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