Perturbation resilience and superiorization methodology of averaged mappings
From MaRDI portal
Publication:5346626
DOI10.1088/1361-6420/33/4/044007zbMath1366.65061OpenAlexW2592837850MaRDI QIDQ5346626
Publication date: 26 May 2017
Published in: Inverse Problems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1088/1361-6420/33/4/044007
quadratic programmingconstrained convex minimizationnumerical resultbounded perturbation resiliencesuperiorizationaveraged mappingsuccessive fixed point algorithm
Numerical mathematical programming methods (65K05) Convex programming (90C25) Quadratic programming (90C20)
Related Items
Strong convergence and bounded perturbation resilience of a modified proximal gradient algorithm ⋮ Feasibility-based fixed point networks ⋮ On perturbed hybrid steepest descent method with minimization or superiorization for subdifferentiable functions ⋮ Bounded perturbation resilience of viscosity proximal algorithm for solving split variational inclusion problems with applications to compressed sensing and image recovery ⋮ Derivative-free superiorization: principle and algorithm
Cites Work
- Unnamed Item
- Three-term conjugate gradient method for the convex optimization problem over the fixed point set of a nonexpansive mapping
- Convergence and perturbation resilience of dynamic string-averaging projection methods
- Projected subgradient minimization versus superiorization
- Strict Fejér monotonicity by superiorization of feasibility-seeking projection methods
- Feasibility-Seeking and Superiorization Algorithms Applied to Inverse Treatment Planning in Radiation Therapy
- Perturbation‐resilient block‐iterative projection methods with application to image reconstruction from projections
- Perturbation resilience and superiorization of iterative algorithms
- A unified treatment of some iterative algorithms in signal processing and image reconstruction
- Accelerated perturbation-resilient block-iterative projection methods with application to image reconstruction
