In this paper, we mainly study the gradient based Jacobi-type algorithms to maximize two classes of homogeneous polynomials with orthogonality constraints, and establish their convergence properties. For the first class of homogeneous polynomials subject to a constraint on a Stiefel manifold, we reformulate it as an optimization problem on a unitary group, which makes it possible to apply the gradient based Jacobi-type (Jacobi-G) algorithm. Then, if the subproblem can be always represented as a quadratic form, we establish the global convergence of Jacobi-G under any one of the three conditions (A1), (A2) and (A3). The convergence result for (A1) is an easy extension of the result in [Usevich et al. SIOPT 2020], while (A2) and (A3) are two new ones. This algorithm and the convergence properties apply to the well-known joint approximate symmetric tensor diagonalization and joint approximate symmetric trace maximization. For the second class of homogeneous polynomials subject to constraints on the product of Stiefel manifolds, we similarly reformulate it as an optimization problem on the product of unitary groups, and then develop a new gradient based multi-block Jacobi-type (Jacobi-MG) algorithm to solve it. We similarly establish the global convergence of Jacobi-MG under any one of the three conditions (A1), (A2) and (A3), if the subproblem can be always represented as a quadratic form. This algorithm and the convergence properties apply to the well-known joint approximate tensor diagonalization and joint approximate tensor compression. As the proximal variants of Jacobi-G and Jacobi-MG, we also propose the Jacobi-GP and Jacobi-MGP algorithms, and establish their global convergence without any further condition. Some numerical results are provided indicating the efficiency of the proposed algorithms.
翻译:在本文中, 我们主要研究基于渐变的雅各比型算法, 以最大限度地增加两种等级的同质多元- G和正方形制约, 并建立它们的趋同特性。 对于一级受斯特里盖尔元体制约的同质多元数组, 我们将其重新定位为一个单一组的优化问题, 这样可以应用基于渐变的雅各基( Jacobi- G) 类型( Jacobi- G) 算法。 然后, 如果子问题可以总是以四分形形式表示, 我们就可以在三种条件( A1, (A2) 和(A3) 中任何一个条件下建立全球同质多级多级多级数组的趋同性趋同, 我们的趋同结果很容易扩大[Usevich 和al. SIO. SIP. 2020], 而 (A2) 和 (A3) 以一个单一的同级数级数级数的算法, 这个算法和合并特性适用于共同的近级数级数分数 。 对于第二个类的多级组, 我们也可以将亚化的变数 的变数 的变数 和亚级的变数, 建立它建立一个以一个 的变数 。