TENSOR RING DECOMPOSITION AND ITS APPLICATIONS

Tensor ring decomposition represents a powerful technique for decomposing high-order tensors. It expresses a tensor as read more a combination of smaller matrices, effectively simplifying its complexity. This decomposition allows for efficient analysis and offers numerous utilization across various domains. In the realm of machine learning, tensor

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 compression of dimensionality leads to significant improvements in terms of storage efficiency and processin