A variant of forward-backward splitting method for the sum of two monotone operators with a new search strategy

DOI10.1080/02331934.2014.883510zbMath1337.49009OpenAlexW1981558178MaRDI QIDQ2808300

R. Díaz Millán, José Yunier Bello Cruz

Publication date: 23 May 2016

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331934.2014.883510

zbMATH Keywords

maximal monotone operatorssplitting methodsArmijo-type search

Mathematics Subject Classification ID

Minimax problems in mathematical programming (90C47) Existence of solutions for minimax problems (49J35)

Related Items

Convergence analysis and applications of the inertial algorithm solving inclusion problems, Two algorithms for solving systems of inclusion problems, A projection algorithm for non-monotone variational inequalities, A relaxed splitting method for solving variational inclusion and fixed point problems, Bregman-Golden ratio algorithms for variational inequalities, Strong convergence of forward-reflected-backward splitting methods for solving monotone inclusions with applications to image restoration and optimal control, A Forward-Backward Splitting Method for Monotone Inclusions Without Cocoercivity, On the weak and strong convergence of modified forward-backward-half-forward splitting methods, Golden ratio algorithms for variational inequalities, Projective splitting with forward steps only requires continuity, Shadow Douglas-Rachford splitting for monotone inclusions

Cites Work

• Unnamed Item
• On the maximal domain of a monotone function
• Convergence of direct methods for paramonotone variational inequalities
• Monotone (nonlinear) operators in Hilbert space
• Ergodic convergence to a zero of the sum of monotone operators in Hilbert space
• A family of projective splitting methods for the sum of two maximal monotone operators
• On some non-linear elliptic differential functional equations
• Convergence theorems for sequences of nonlinear operators in Banach spaces
• Proximal Splitting Methods in Signal Processing
• A Strongly Convergent Method for Nonsmooth Convex Minimization in Hilbert Spaces
• A Strongly Convergent Direct Method for Monotone Variational Inequalities in Hilbert Spaces
• Splitting Algorithms for the Sum of Two Nonlinear Operators
• A New Projection Method for Variational Inequality Problems
• A variant of korpelevich’s method for variational inequalities with a new search strategy
• A new proximal point iteration that converges weakly but not in norm
• Entropy-Like Proximal Methods in Convex Programming
• On Projection Algorithms for Solving Convex Feasibility Problems
• A Modified Forward-Backward Splitting Method for Maximal Monotone Mappings
• Convex analysis and monotone operator theory in Hilbert spaces