A Numerical Study of the Limited Memory BFGS Method and the Truncated-Newton Method for Large Scale Optimization
From MaRDI portal
Publication:4012415
DOI10.1137/0801023zbMath0756.65091OpenAlexW2124812425MaRDI QIDQ4012415
Nocedal, Jorge, Stephen G. Nash
Publication date: 27 September 1992
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1137/0801023
performanceconjugate gradient methodtest problemslarge scale optimizationtruncated-Newton methodsmooth unconstrained minimizationlimited memory Broyden-Fletcher-Goldfarb-Shanno method
Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Nonlinear programming (90C30)
Related Items
A sparse nonlinear optimization algorithm, An unconstrained optimization technique for large-scale linearly constrained convex minimization problems, Aerodynamic design using the truncated Newton algorithm and the continuous adjoint approach, Truncated regularized Newton method for convex minimizations, A truncated Newton optimization algorithm in meteorology applications with analytic Hessian/vector products, A Globally Convergent Trust-Region Method for Large-Scale Symmetric Nonlinear Systems, Optimal assimilation of current and surface elevation data in a two-dimensional numerical tidal model, Best practices for comparing optimization algorithms, On the efficiency of gradient based optimization algorithms for DNS-based optimal control in a turbulent channel flow, On Efficiently Computing the Eigenvalues of Limited-Memory Quasi-Newton Matrices, A new class of supermemory gradient methods, An incomplete Hessian Newton minimization method and its application in a chemical database problem, Efficiently preconditioned inexact Newton methods for large symmetric eigenvalue problems, An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization, Diagonal approximation of the Hessian by finite differences for unconstrained optimization, Limited memory preconditioners for symmetric indefinite problems with application to structural mechanics, Low-rank update of preconditioners for the inexact Newton method with SPD Jacobian, A new regularized limited memory BFGS-type method based on modified secant conditions for unconstrained optimization problems, Full Waveform Inversion and the Truncated Newton Method, Truncated-Newton training algorithm for neurocomputational viscoplastic model., An accelerated subspace minimization three-term conjugate gradient algorithm for unconstrained optimization, Multigrid optimization for DNS-based optimal control in turbulent channel flows, A Hessian-free Newton-Raphson method for the configuration of physics systems featured by numerically asymmetric force field, Damped techniques for the limited memory BFGS method for large-scale optimization, A regularized limited memory BFGS method for nonconvex unconstrained minimization, Sensitivity analysis of the strain criterion for multidimensional scaling, A class of diagonal preconditioners for limited memory BFGS method, Extra-updates criterion for the limited memory BFGS algorithm for large scale nonlinear optimization, The trust region subproblem and semidefinite programming*, A new three-term conjugate gradient algorithm for unconstrained optimization, Dynamic scaling based preconditioning for truncated Newton methods in large scale unconstrained optimization, A server for automated performance analysis of benchmarking data, On the resolution of monotone complementarity problems, An Analysis of a Hybrid Optimization Method for Variational Data Assimilation, The adjoint Newton algorithm for large-scale unconstrained optimization in meteorology applications, Assessing the performance of an optimization-based multilevel method, Block preconditioners for linear systems in interior point methods for convex constrained optimization, A survey of truncated-Newton methods
Uses Software
