TENSOR RING DECOMPOSITION AND ITS APPLICATIONS

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 decomposition allows for efficient computation and offers numerous applications across various domains. In the realm of machine learning, tensor ring decomposi

Tensor rings provide a novel and powerful framework for optimal representation learning. By decomposing high-order tensors into a sum of lower-rank tensors, tensor ring models capture complex data structures in a more compact manner. This compression of dimensionality leads to significant advantages in terms of space efficiency and processing speed