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Approximate Matrix and Tensor Diagonalization by Unitary Transformations: Convergence of Jacobi-Type Algorithms
SIAM Journal on Optimization ( IF 2.6 ) Pub Date : 2020-10-19 , DOI: 10.1137/19m125950x
Konstantin Usevich , Jianze Li , Pierre Comon

SIAM Journal on Optimization, Volume 30, Issue 4, Page 2998-3028, January 2020.
We propose a gradient-based Jacobi algorithm for a class of maximization problems on the unitary group, with a focus on approximate diagonalization of complex matrices and tensors by unitary transformations. We provide weak convergence results, and prove local linear convergence of this algorithm. The convergence results also apply to the case of real-valued tensors.


中文翻译:

Unit变换的近似矩阵和张量对角化:Jacobi型算法的收敛性

SIAM优化杂志,第30卷,第4期,第2998-3028页,2020年1月。
我们针对for群上的一类最大化问题提出了一种基于梯度的Jacobi算法,重点是通过复矩阵和张量的近似对角化单一变换。我们提供了较弱的收敛结果,并证明了该算法的局部线性收敛。收敛结果也适用于实值张量的情况。
更新日期:2020-11-13
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