Barzilai–Borwein method with variable sample size for stochastic linear complementarity problems

DOI10.1080/02331934.2015.1062008zbMath1332.90304OpenAlexW2231908178MaRDI QIDQ2790891

Sanja Rapajić, Nataša Krklec Jerinkić, Nataša Krejić

Publication date: 8 March 2016

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331934.2015.1062008

zbMATH Keywords

nonsmooth systemsnonmonotone line searchsample average approximationstochastic linear complementarity problemsvariable sample size

Mathematics Subject Classification ID

Numerical computation of solutions to systems of equations (65H10) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33)

Related Items (3)

Stochastic \(R_0\) matrix linear complementarity problems: the Fischer-Burmeister function-based expected residual minimization ⋮ Accelerated augmented Lagrangian method for total variation minimization ⋮ An inexact restoration-nonsmooth algorithm with variable accuracy for stochastic nonsmooth convex optimization problems in machine learning and stochastic linear complementarity problems

Cites Work

• Feasible smooth method based on Barzilai-Borwein method for stochastic linear complementarity problem
• Robust solution of monotone stochastic linear complementarity problems
• An affine-scaling interior-point CBB method for box-constrained optimization
• Globally convergent Jacobian smoothing inexact Newton methods for NCP
• A class of smoothing functions for nonlinear and mixed complementarity problems
• Line search methods with variable sample size for unconstrained optimization
• Nonmonotone line search methods with variable sample size
• The Barzilai and Borwein Gradient Method for the Large Scale Unconstrained Minimization Problem
• Smoothing Projected Gradient Method and Its Application to Stochastic Linear Complementarity Problems
• Two-Point Step Size Gradient Methods
• Global and superlinear convergence of the smoothing Newton method and its application to general box constrained variational inequalities
• Jacobian Smoothing Methods for Nonlinear Complementarity Problems
• Expected Residual Minimization Method for Stochastic Linear Complementarity Problems

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