Self-Adaptive Inertial Projection and Contraction Algorithm for Monotone Variational Inequality

DOI10.1142/S0217595921500214zbMath1496.49006OpenAlexW3162456388MaRDI QIDQ5865921

Xue Gao, Xueye Wang, Xing-Ju Cai

Publication date: 10 June 2022

Published in: Asia-Pacific Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0217595921500214

zbMATH Keywords

Hilbert spacemonotone variational inequalitybacktracking searchinertial projection and contraction algorithm

Mathematics Subject Classification ID

Variational inequalities (49J40) Existence theories for problems in abstract spaces (49J27)

Uses Software

• iPiano
• iPiasco

Cites Work

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• Inertial Douglas-Rachford splitting for monotone inclusion problems
• On the \(O(1/t)\) convergence rate of the projection and contraction methods for variational inequalities with Lipschitz continuous monotone operators
• The subgradient extragradient method for solving variational inequalities in Hilbert space
• iPiasco: inertial proximal algorithm for strongly convex optimization
• An iterative algorithm for the variational inequality problem
• Inertial projection and contraction algorithms for variational inequalities
• A class of projection and contraction methods for monotone variational inequalities
• Fast convergence of inertial dynamics and algorithms with asymptotic vanishing viscosity
• The extragradient algorithm with inertial effects for solving the variational inequality
• iPiano: Inertial Proximal Algorithm for Nonconvex Optimization
• Strong convergence of subgradient extragradient methods for the variational inequality problem in Hilbert space
• Weak Convergence of a Relaxed and Inertial Hybrid Projection-Proximal Point Algorithm for Maximal Monotone Operators in Hilbert Space
• A simple proof for some important properties of the projection mapping
• A Dynamical Approach to an Inertial Forward-Backward Algorithm for Convex Minimization
• Some methods of speeding up the convergence of iteration methods
• A Descent Lemma Beyond Lipschitz Gradient Continuity: First-Order Methods Revisited and Applications
• Convex analysis and monotone operator theory in Hilbert spaces
• An inertial proximal method for maximal monotone operators via discretization of a nonlinear oscillator with damping
• A modified alternating direction method for variational inequality problems.
• Improvements of some projection methods for monotone nonlinear variational inequalities

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