A new generalized cyclic symmetric structure in the factor matrices of polyadic decompositions of matrix multiplication tensors for non-square matrix multiplication is proposed to reduce the number of variables in the optimization problem and in this way improve the convergence. The structure is implemented in an existing numerical optimization algorithm. Extensive numerical experiments are given that the proposed structure indeed finds more (practical) decompositions.

翻译：本文针对非方阵乘法张量的多分量分解，提出了一种新的广义循环对称因子矩阵结构，旨在减少优化问题中的变量数量，从而改善收敛性。该结构已在现有数值优化算法中实现。大量数值实验表明，所提出的结构确实能够发现更多（实用性的）分解形式。