A Jacobi-Like Method for the Automatic Computation of Eigenvalues and Eigenvectors of an Arbitrary Matrix

By P. J. Ebertein. 1962

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Beyond CCA: Moment Matching for Multi-View Models (2016, background): “Indeed, in such case, NOJD boils down to an algorithm for a non-symmetric eigenproblem (Eberlein, 1962; Ruhe, 1968).”
On the quadratic convergence of a generalization of the Jacobi Method to arbitrary matrices (1968, methodology): “Eberlein [ 3 ] and Rutishauser [16] have devised such methods, the former using plane shears and the latter using diagonal similarities.”
Simultaneous Diagonalization With Similarity Transformation for Non-Defective Matrices (2006, background): “For the shear transformation, after choosing h, we follow [8], ‖Ah‖(2)F = (cosh 2y − 1)Gh − 2 sinh 2y · Kh + sinh(2) 2y · (d(2)h + ξ(2) h) + sinh 4y · ξhdh + ‖Ah‖(2)F (13)”
Hamilton and Jacobi come full circle: Jacobi algorithms for structured Hamiltonian eigenproblems (2001, unknown): “Originally designed to work on symmetric matrices via plane rotations targeting 2 × 2 subproblems, Jacobi’s method [34] has been adapted to several other classes of matrices (see for example, [10,12,18,24,26,50]).”