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Penalty-proximal methods in convex programming
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Necessary and sufficient conditions for a penalty method to be exact
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A descent algorithm for nonsmooth convex optimization
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A method of conjugate subgradients for minimizing nondifferentiable functions
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Numerical methods for nondifferentiable convex optimization
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An algorithm for linearly constrained convex nondifferentiable minimization problems
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MONOTONE OPERATORS AND AUGMENTED LAGRANGIAN METHODS IN NONLINEAR PROGRAMMING
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ON A BUNDLE ALGORITHM FOR NONSMOOTH OPTIMIZATION
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Programmation mathématique convexe
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An Exact Penalty Function Algorithm for Non-smooth Convex Constrained Minimization Problems
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Monotone Operators and the Proximal Point Algorithm
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Iterative Solution of Linear Programs
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Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
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A Superlinearly Convergent Algorithm for One-Dimensional Constrained Minimization Problems with Convex Functions
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Sensitivity and stability in NLP ILL-POSED VARIATIONAL PROBLEMS
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Proximal Methods for Variational Inequalities with Set-Valued Monotone Operators
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Cost Approximation Algorithms
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Ill-posed Variational Problems
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Convex Optimization in Normed Spaces: Theory, Methods and Examples
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Mixing proximal regularization, penalization and parallel decomposition in convex programming
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Convergence Analysis of a Perturbed Version of the θ — Scheme of Glowinski-Le Tallec
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Multi–Step Proximal Method for Variational Inequalities with Monotone Operators
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Convergence of diagonally stationary sequences in convex optimization
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The perturbed proximal point algorithm and some of its applications
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Exact penalty functions in proximal bundle methods for constrained convex nondifferentiable minimization
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A continuation method for monotone variational inequalities
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Penalization in non-classical convex programming via variational convergence
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Family of perturbation methods for variational inequalities
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Equilibrium programming using proximal-like algorithms
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Strong convergence of a proximal-based method for convex optimization
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Primal and dual convergence of a proximal point exponential penalty method for linear programming
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Computing proximal points of nonconvex functions
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Iterative Regularization via Dual Diagonal Descent
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Coupling the Gradient Method with a General Exterior Penalization Scheme for Convex Minimization
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Dual Convergence for Penalty Algorithms in Convex Programming
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Lagrangian Penalization Scheme with Parallel Forward–Backward Splitting
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Lagrangian-Penalization Algorithm for Constrained Optimization and Variational Inequalities
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Alternating forward–backward splitting for linearly constrained optimization problems
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Mathematical Background
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Convex Programming
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Optimal Control of Hybrid and Switched Systems
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Applications of the Relaxation-Based Approach
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Alternating proximal algorithms for linearly constrained variational inequalities: Application to domain decomposition for PDE’s
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Proximal Point Methods and Nonconvex Optimization
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Prox-regularization and solution of ill-posed elliptic variational inequalities
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Coupling the Proximal Point Algorithm with Approximation Methods
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Proximal Methods in View of Interior-Point Strategies
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The perturbed Tikhonov's algorithm and some of its applications
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Proximal-type methods with generalized Bregman functions and applications to generalized fractional programming
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On the convergence of the proximal algorithm for saddle-point problems
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Proximal interior point approach in convex programming (ill-posed problems)*†
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Survey of Bundle Methods for Nonsmooth Optimization
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Iterative regularization in classification via hinge loss diagonal descent
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A Perturbed Parallel Decomposition Method for a Class of Nonsmooth Convex Minimization Problems
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Prox-Penalization and Splitting Methods for Constrained Variational Problems
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Proximal Point Approach and Approximation of Variational Inequalities
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Coupling General Penalty Schemes for Convex Programming with the Steepest Descent and the Proximal Point Algorithm
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Proximal Point Algorithm Controlled by a Slowly Vanishing Term: Applications to Hierarchical Minimization
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Theoretical Aspect of Diagonal Bregman Proximal Methods
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Convergence of a Hybrid Projection-Proximal Point Algorithm Coupled with Approximation Methods in Convex Optimization
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Bounded Diagonally Stationary Sequences in Convex Optimization
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Asymptotic Convergence to the Optimal Value of Diagonal Proximal Iterations in Convex Minimization
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Comportement asymptotique de systèmes dynamiques discrets et continus en Optimisation et EDP : algorithmes de minimisation proximale alternée et dynamique du deuxieme ordre à dissipation évanescente.
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