Tensor ring decomposition employs a powerful technique for understanding high-order tensors. It expresses a tensor as a sum of smaller matrices, effectively simplifying its complexity. This factorization allows for efficient analysis and offers numerous utilization across various domains. In the realm of data science, tensor ring decomposition ena… Read More

Tensor rings provide a novel and powerful framework for effective representation learning. By decomposing high-order tensors into a sum of lower-rank tensors, tensor ring models model complex data structures in a more compressed manner. This decomposition of dimensionality leads to significant advantages in terms of memory efficiency and inference … Read More