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The Riemannian two-step perturbed Gauss-Newton method for least squares inverse eigenvalue problems.
Zhi Zhao
Xiao-Qing Jin
Teng-Teng Yao
Published in:
J. Comput. Appl. Math. (2022)
Keyphrases
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least squares
newton method
eigenvalue problems
regularized least squares
convergence analysis
nonnegative matrix factorization
optimality conditions
linear equations
linear regression
variational inequalities
optical flow
linear programming
dynamical systems
global convergence