A Levenberg-Marquardt method for large nonlinear least-squares problems with dynamic accuracy in functions and gradients
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Publication:1616028
DOI10.1007/s00211-018-0977-zzbMath1461.65129OpenAlexW2810507125MaRDI QIDQ1616028
Elisa Riccietti, Stefania Bellavia, Serge Gratton
Publication date: 31 October 2018
Published in: Numerische Mathematik (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00211-018-0977-z
Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30)
Related Items (11)
A Stochastic Levenberg--Marquardt Method Using Random Models with Complexity Results ⋮ Efficient parameters estimation method for the separable nonlinear least squares problem ⋮ Convergence analysis of a subsampled Levenberg-Marquardt algorithm ⋮ Numerical linear algebra in data assimilation ⋮ A note on solving nonlinear optimization problems in variable precision ⋮ Globally Convergent Multilevel Training of Deep Residual Networks ⋮ Newton-MR: inexact Newton method with minimum residual sub-problem solver ⋮ A modified inexact Levenberg-Marquardt method with the descent property for solving nonlinear equations ⋮ Majorization-minimization-based Levenberg-Marquardt method for constrained nonlinear least squares ⋮ A split Levenberg-Marquardt method for large-scale sparse problems ⋮ Adaptive Regularization Algorithms with Inexact Evaluations for Nonconvex Optimization
Uses Software
Cites Work
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