Tensor ring decomposition represents a powerful technique for analyzing high-order tensors. It expresses a tensor as a product of smaller matrices, effectively reducing its complexity. This factorization allows for efficient processing and offers numerous utilization across various domains.

Tensor rings provide a novel and powerful framework for efficient representation learning. By decomposing high-order tensors into a sum of lower-rank tensors, tensor ring models model complex data structures in a more compact manner. This reduction of dimensionality leads to significant advantage