Multi-step-prox-regularization method for solving convex variation problems
DOI10.1080/02331939508844083zbMath0820.65035OpenAlexW2003119630MaRDI QIDQ4836771
Rainer Tichatschke, Alexander Kaplan
Publication date: 21 June 1995
Published in: Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331939508844083
convergenceiteration methodadaptive approximationiterative prox-regularizationill- posed convex variational problems
Numerical optimization and variational techniques (65K10) Quadratic programming (90C20) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Optimality conditions for problems in abstract spaces (49K27)
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Cites Work
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- Penalization in non-classical convex programming via variational convergence
- Primal-dual proximal point algorithm for linearly constrained convex programming problems
- Produits infinis de resolvantes
- Iterative processes for solving incorrect convex variational problems
- Convergence of convex sets and of solutions of variational inequalities
- Asymptotic Convergence Analysis of the Proximal Point Algorithm
- A Generalization of the Proximal Point Algorithm
- Applications of the method of partial inverses to convex programming: Decomposition
- On the Convergence of the Proximal Point Algorithm for Convex Minimization
- Discrete approximations of minimization problems. I. Theory
- Monotone Operators and the Proximal Point Algorithm
- Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
- Variatoinal inequalities and convex semi-infinite programming problems
- A regularized penalty method for solving convex semi-infinite programs
- Numerical methods for nondifferentiable convex optimization
- Weak convergence of the sequence of successive approximations for nonexpansive mappings
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