EFFICIENT REPRESENTATION LEARNING WITH TENSOR RINGS

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 represent complex data structures in a more compact manner. This reduction of dimensionality leads to significant advantages in terms of space efficiency and processing speed