A derivative-free Gauss-Newton method
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Publication:2295977
DOI10.1007/s12532-019-00161-7zbMath1461.65136arXiv1710.11005OpenAlexW2963837723WikidataQ127862149 ScholiaQ127862149MaRDI QIDQ2295977
Lindon Roberts, Coralia Cartis
Publication date: 17 February 2020
Published in: Mathematical Programming Computation (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1710.11005
least-squaresderivative-free optimizationworst-case complexityGauss-Newton methodtrust region methods
Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Derivative-free methods and methods using generalized derivatives (90C56) Software, source code, etc. for problems pertaining to operations research and mathematical programming (90-04)
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Cites Work
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- On the local convergence of a derivative-free algorithm for least-squares minimization
- Updating the regularization parameter in the adaptive cubic regularization algorithm
- Recent progress in unconstrained nonlinear optimization without derivatives
- On trust region methods for unconstrained minimization without derivatives
- UOBYQA: unconstrained optimization by quadratic approximation
- Least Frobenius norm updating of quadratic models that satisfy interpolation conditions
- Hybrid methods for large sparse nonlinear least squares
- A derivative-free trust-region algorithm for composite nonsmooth optimization
- A derivative-free Gauss-Newton method
- CUTEst: a constrained and unconstrained testing environment with safe threads for mathematical optimization
- Geometry of interpolation sets in derivative free optimization
- Trust-Region Methods Without Using Derivatives: Worst Case Complexity and the NonSmooth Case
- Global Convergence of Radial Basis Function Trust-Region Algorithms for Derivative-Free Optimization
- Self-Correcting Geometry in Model-Based Algorithms for Derivative-Free Unconstrained Optimization
- A Derivative-Free Algorithm for Least-Squares Minimization
- Levenberg--Marquardt Methods Based on Probabilistic Gradient Models and Inexact Subproblem Solution, with Application to Data Assimilation
- Introduction to Derivative-Free Optimization
- ORBIT: Optimization by Radial Basis Function Interpolation in Trust-Regions
- Dud, A Derivative-Free Algorithm for Nonlinear Least Squares
- Testing Unconstrained Optimization Software
- Trust Region Methods
- Function Minimization by Interpolation in a Data Table
- Benchmarking Derivative-Free Optimization Algorithms
- Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points
- Cluster Newton Method for Sampling Multiple Solutions of Underdetermined Inverse Problems: Application to a Parameter Identification Problem in Pharmacokinetics
