An improvement of adaptive cubic regularization method for unconstrained optimization problems
From MaRDI portal
Publication:5031220
DOI10.1080/00207160.2020.1738406zbMath1495.65077OpenAlexW3010558735MaRDI QIDQ5031220
No author found.
Publication date: 18 February 2022
Published in: International Journal of Computer Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207160.2020.1738406
unconstrained optimizationglobal convergencenonmonotone line searchcubic regularizationARC algorithm
Related Items
A cubic regularization of Newton's method with finite difference Hessian approximations ⋮ Two modified adaptive cubic regularization algorithms by using the nonmonotone Armijo-type line search ⋮ A filter sequential adaptive cubic regularization algorithm for nonlinear constrained optimization ⋮ A sequential adaptive regularisation using cubics algorithm for solving nonlinear equality constrained optimization ⋮ A smoothing Newton method with a mixed line search for monotone weighted complementarity problems
Uses Software
Cites Work
- An efficient nonmonotone trust-region method for unconstrained optimization
- Interior-point methods for nonconvex nonlinear programming: cubic regularization
- Adaptive cubic regularisation methods for unconstrained optimization. I: Motivation, convergence and numerical results
- Adaptive cubic regularisation methods for unconstrained optimization. II: Worst-case function- and derivative-evaluation complexity
- Updating the regularization parameter in the adaptive cubic regularization algorithm
- Accelerating the cubic regularization of Newton's method on convex problems
- A truncated Newton method with non-monotone line search for unconstrained optimization
- On the use of the energy norm in trust-region and adaptive cubic regularization subproblems
- A nonmonotone trust-region line search method for large-scale unconstrained optimization
- Cubic regularization of Newton method and its global performance
- On the use of iterative methods in cubic regularization for unconstrained optimization
- A cubic regularization algorithm for unconstrained optimization using line search and nonmonotone techniques
- Testing Unconstrained Optimization Software
- The watchdog technique for forcing convergence in algorithms for constrained optimization
- Trust Region Methods
- A new conjugate gradient algorithm with cubic Barzilai–Borwein stepsize for unconstrained optimization
- A Nonmonotone Line Search Technique and Its Application to Unconstrained Optimization
- A Nonmonotone Line Search Technique for Newton’s Method
- Gradient Descent Finds the Cubic-Regularized Nonconvex Newton Step
- Modified Gauss–Newton scheme with worst case guarantees for global performance
- Benchmarking optimization software with performance profiles.
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: An improvement of adaptive cubic regularization method for unconstrained optimization problems
