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 compact manner. This compression of dimensionality leads to significant improvements in terms of memory efficiency and inference