Tensor Ring Decomposition and its Applications

Tensor ring decomposition represents a powerful technique for analyzing high-order tensors. It expresses a tensor as a sum of smaller matrices, effectively simplifying its complexity. This factorization allows for efficient computation and offers numerous implementations across various domains.

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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 model complex data structures in a more compressed manner. This decomposition of dimensionality leads to significant bene

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