SIAM Journal on Control and Optimization
Finite termination of the proximal point algorithm
Mathematical Programming: Series A and B
Mathematical Programming: Series A and B
Nonlinear proximal point algorithms using Bregman functions, with applications to convex programming
Mathematics of Operations Research
Approximate iterations in Bregman-function-based proximal algorithms
Mathematical Programming: Series A and B
A Modified Forward-Backward Splitting Method for Maximal Monotone Mappings
SIAM Journal on Control and Optimization
Mathematics of Operations Research
Alternating Projection-Proximal Methods for Convex Programming and Variational Inequalities
SIAM Journal on Optimization
Local Convergence of the Proximal Point Algorithm and Multiplier Methods Without Monotonicity
Mathematics of Operations Research
A new system of variational inclusions with (H, η)-monotone operators in hilbert spaces
Computers & Mathematics with Applications
Hi-index | 0.98 |
A general framework for the Eckstein-Bertsekas proximal point algorithm, based on the notion of (H,@h)-monotonicity, is developed. Convergence analysis for the generalized Eckstein-Bertsekas proximal point algorithm in the context of solving a class of nonlinear inclusions is examined. Furthermore, some results on general firm nonexpansiveness and resolvent mapping corresponding to (H,@h)-monotonicity are given.