A regularized Newton method for degenerate unconstrained optimization problems

DOI10.1007/s11590-011-0386-zzbMath1258.90106OpenAlexW2032158421MaRDI QIDQ1926636

Yumei Liang, Chungen Shen, Xiongda Chen

Publication date: 28 December 2012

Published in: Optimization Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11590-011-0386-z

zbMATH Keywords

superlinear convergencesecond-order conditionregularized method

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Methods of quasi-Newton type (90C53)

Related Items (9)

Convergence analysis of a regularized interior point algorithm for the barrier problems with singular solutions ⋮ A fast and simple modification of Newton's method avoiding saddle points ⋮ A multi-step class of iterative methods for nonlinear systems ⋮ An inexact proximal regularization method for unconstrained optimization ⋮ Local convergence analysis of a primal-dual method for bound-constrained optimization without SOSC ⋮ On the final steps of Newton and higher order methods ⋮ A regularized Newton method without line search for unconstrained optimization ⋮ Two nonmonotone trust region algorithms based on an improved Newton method ⋮ Correction of trust region method with a new modified Newton method

Uses Software

• CUTEr
• levmar
• CUTE

Cites Work

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• Combining and scaling descent and negative curvature directions
• Levenberg--Marquardt methods with strong local convergence properties for solving nonlinear equations with convex constraints
• Convergence properties of the regularized Newton method for the unconstrained nonconvex optimization
• Convergence rate of the trust region method for nonlinear equations under local error bound condition
• Computing a nearest symmetric positive semidefinite matrix
• A unified local convergence analysis of inexact constrained Levenberg-Marquardt methods
• On the quadratic convergence of the Levenberg-Marquardt method without nonsingularity assumption
• Superlinear convergence of a Newton-type algorithm for monotone equations
• Regularized Newton methods for convex minimization problems with singular solutions
• A Modified Cholesky Algorithm Based on a Symmetric Indefinite Factorization
• Accurate Symmetric Indefinite Linear Equation Solvers
• CUTE
• Convergence Properties of the Inexact Levenberg-Marquardt Method under Local Error Bound Conditions

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