Tensor ring decomposition represents a powerful technique for analyzing high-order tensors. It expresses a tensor as a sum of smaller matrices, effectively representing its complexity. This representation allows for efficient processing and offers numerous applications across various domains. In the realm of data science, tensor ring decomposition… Read More

Tensor rings provide a novel and powerful framework for efficient representation learning. By decomposing high-order tensors into a sum of lower-rank tensors, tensor ring models model complex data structures in a more compact manner. This reduction of dimensionality leads to significant advantages in terms of space efficiency and computational spee… Read More