A structured diagonal Hessian approximation method with evaluation complexity analysis for nonlinear least squares
From MaRDI portal
Publication:1715713
DOI10.1007/s40314-018-0696-1zbMath1413.90268OpenAlexW2888991842MaRDI QIDQ1715713
Hassan Mohammad, Sandra Augusta Santos
Publication date: 29 January 2019
Published in: Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s40314-018-0696-1
global convergencecomputational resultsnonlinear least squares problemslarge-scale problemsevaluation complexityJacobian-free strategy
Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Nonlinear programming (90C30) Numerical methods based on nonlinear programming (49M37)
Related Items
On the Barzilai–Borwein gradient methods with structured secant equation for nonlinear least squares problems, A derivative-free multivariate spectral projection algorithm for constrained nonlinear monotone equations, Two diagonal conjugate gradient like methods for unconstrained optimization, Structured two-point stepsize gradient methods for nonlinear least squares, Structured adaptive spectral-based algorithms for nonlinear least squares problems with robotic arm modelling applications, Unnamed Item, A brief survey of methods for solving nonlinear least-squares problems, A structured quasi-Newton algorithm with nonmonotone search strategy for structured NLS problems and its application in robotic motion control, A diagonal PRP-type projection method for convex constrained nonlinear monotone equations, Worst-case evaluation complexity of derivative-free nonmonotone line search methods for solving nonlinear systems of equations, Structured spectral algorithm with a nonmonotone line search for nonlinear least squares, Structured diagonal Gauss-Newton method for nonlinear least squares
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Local analysis of a spectral correction for the Gauss-Newton model applied to quadratic residual problems
- Jacobian-free implicit inner-iteration preconditioner for nonlinear least squares problems
- A literature survey of benchmark functions for global optimisation problems
- A secant method for nonlinear least-squares minimization
- On the convergence and worst-case complexity of trust-region and regularization methods for unconstrained optimization
- Worst-case evaluation complexity for unconstrained nonlinear optimization using high-order regularized models
- Regularized nonlinear least squares methods for hit position reconstruction in small gamma cameras
- Multivariate spectral gradient method for unconstrained optimization
- Nonlinear conjugate gradient methods with structured secant condition for nonlinear least squares problems
- Numerical experiments with variations of the Gauss-Newton algorithm for nonlinear least squares
- Solving the nonlinear least square problem: Application of a general method
- Jacobian-free Newton-Krylov methods: a survey of approaches and applications.
- A Levenberg--Marquardt scheme for nonlinear image registration
- Hybrid methods for large sparse nonlinear least squares
- Maximum likelihood least squares identification method for input nonlinear finite impulse response moving average systems
- An inexact and nonmonotone proximal method for smooth unconstrained minimization
- Optimization theory and methods. Nonlinear programming
- Global complexity bound of the Levenberg–Marquardt method
- On the Evaluation Complexity of Cubic Regularization Methods for Potentially Rank-Deficient Nonlinear Least-Squares Problems and Its Relevance to Constrained Nonlinear Optimization
- Convergence of a Regularized Euclidean Residual Algorithm for Nonlinear Least-Squares
- A Derivative-Free Algorithm for Least-Squares Minimization
- The Barzilai and Borwein Gradient Method for the Large Scale Unconstrained Minimization Problem
- The Modified Gauss-Newton Method for the Fitting of Non-Linear Regression Functions by Least Squares
- Variational Methods for Non-Linear Least-Squares
- Two-Point Step Size Gradient Methods
- Hybrid Methods for Nonlinear Least Squares
- An Algorithm for Least-Squares Estimation of Nonlinear Parameters
- Some Recent Approaches to Solving Large Residual Nonlinear Least Squares Problems
- Testing Unconstrained Optimization Software
- An Adaptive Nonlinear Least-Squares Algorithm
- Specialised versus general-purpose algorithms for minimising functions that are sums of squared terms
- The estimation of the hessian matrix in nonlinear least squares problems with non-zero residuals
- On the Use of Product Structure in Secant Methods for Nonlinear Least Squares Problems
- Separable nonlinear least squares: the variable projection method and its applications
- A Nonmonotone Line Search Technique and Its Application to Unconstrained Optimization
- A Nonmonotone Line Search Technique for Newton’s Method
- On the Evaluation Complexity of Constrained Nonlinear Least-Squares and General Constrained Nonlinear Optimization Using Second-Order Methods
- On the Barzilai and Borwein choice of steplength for the gradient method
- Function minimization by conjugate gradients
- Modified Gauss–Newton scheme with worst case guarantees for global performance
- Spectral residual method without gradient information for solving large-scale nonlinear systems of equations
- A Method for Minimizing a Sum of Squares of Non-Linear Functions Without Calculating Derivatives
- A method for the solution of certain non-linear problems in least squares
- Benchmarking optimization software with performance profiles.