A fast stochastic approximation-based subgradient extragradient algorithm with variance reduction for solving stochastic variational inequality problems

DOI10.1016/j.cam.2022.114786zbMath1497.65102OpenAlexW4294805110WikidataQ114201635 ScholiaQ114201635MaRDI QIDQ2087495

Yue-Hong He, Xian-Jun Long

Publication date: 21 October 2022

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2022.114786

zbMATH Keywords

stochastic approximationvariance reductionline searchstochastic variational inequalitysubgradient extragradient algorithm

Mathematics Subject Classification ID

Stochastic programming (90C15) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33) Numerical methods for variational inequalities and related problems (65K15)

Related Items (3)

Modified subgradient extragradient algorithms with a new line-search rule for variational inequalities ⋮ A stochastic projection and contraction algorithm with inertial effects for stochastic variational inequalities ⋮ Randomized Lagrangian stochastic approximation for large-scale constrained stochastic Nash games

Cites Work

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• The subgradient extragradient method for solving variational inequalities in Hilbert space
• On smoothing, regularization, and averaging in stochastic approximation methods for stochastic variational inequality problems
• On stochastic mirror-prox algorithms for stochastic Cartesian variational inequalities: randomized block coordinate and optimal averaging schemes
• On the analysis of variance-reduced and randomized projection variants of single projection schemes for monotone stochastic variational inequality problems
• Variance-based subgradient extragradient method for stochastic variational inequality problems
• Variational analysis perspective on linear convergence of some first order methods for nonsmooth convex optimization problems
• An infeasible stochastic approximation and projection algorithm for stochastic variational inequalities
• Optimal stochastic extragradient schemes for pseudomonotone stochastic variational inequality problems and their variants
• Incremental constraint projection methods for variational inequalities
• On the convergence properties of non-Euclidean extragradient methods for variational inequalities with generalized monotone operators
• A class of projection and contraction methods for monotone variational inequalities
• Self-Tuned Stochastic Approximation Schemes for Non-Lipschitzian Stochastic Multi-User Optimization and Nash Games
• Engineering and Economic Applications of Complementarity Problems
• Variance-Based Extragradient Methods with Line Search for Stochastic Variational Inequalities
• Finite-Dimensional Variational Inequalities and Complementarity Problems
• Stochastic Approximation Approaches to the Stochastic Variational Inequality Problem
• Hybrid inertial subgradient extragradient methods for variational inequalities and fixed point problems involving asymptotically nonexpansive mappings
• Two inertial subgradient extragradient algorithms for variational inequalities with fixed-point constraints
• Minibatch Forward-Backward-Forward Methods for Solving Stochastic Variational Inequalities
• Variance-Based Modified Backward-Forward Algorithm with Line Search for Stochastic Variational Inequality Problems and Its Applications
• Incremental Constraint Projection Methods for Monotone Stochastic Variational Inequalities
• Regularized Iterative Stochastic Approximation Methods for Stochastic Variational Inequality Problems
• A Stochastic Approximation Method
• Convex analysis and monotone operator theory in Hilbert spaces

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