Jacobi-type algorithm for low rank orthogonal approximation of symmetric tensors and its convergence analysis

In this paper, we propose a Jacobi-type algorithm to solve the low rank orthogonal approximation problem of symmetric tensors. This algorithm includes as a special case the well-known Jacobi CoM2 algorithm for the approximate orthogonal diagonalization problem of symmetric tensors. We study the global convergence of this algorithm under a gradient based ordering for a special case: the best rank-2 orthogonal approximation of 3rd order symmetric tensors, and prove that an accumulation point is the unique limit point under some conditions. We also propose a proximal variant of this algorithm in general case, and prove its global convergence without any further condition. Numerical experiments are presented to show the efficiency of this algorithm.