EFFICIENT REPRESENTATION LEARNING WITH TENSOR RINGS

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 represent complex data structures in a more sparse manner. This decomposition of dimensionality leads to significant advantages in terms of storage efficiency and inference