Newton-Goldstein convergence rates for convex constrained minimization problems with singular solutions

DOI10.1007/BF01449042zbMath0559.65043OpenAlexW2067577025MaRDI QIDQ2266355

Yanyan Li

Publication date: 1984

Published in: Applied Mathematics and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01449042

zbMATH Keywords

singular solutionssuperlinear convergencelocal quadratic approximationquadratic subproblemsconvex constrained minimization problemsiterative minimization methodsNewton-Goldstein convergence rates

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25)

Related Items (6)

A projected Newton method in a Cartesian product of balls ⋮ A projected Newton method for minimization problems with nonlinear inequality constraints ⋮ Variable metric gradient projection processes in convex feasible sets defined by nonlinear inequalities ⋮ Convergence of algorithms for perturbed optimization problems ⋮ On the convergence of projected gradient processes to singular critical points ⋮ Newton's method for singular constrained optimization problems

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