Lagrangian penalization scheme with parallel forward-backward splitting
From MaRDI portal
Publication:725876
DOI10.1007/s10957-018-1265-xzbMath1396.49032OpenAlexW2792910584WikidataQ130083108 ScholiaQ130083108MaRDI QIDQ725876
Cesare Molinari, Juan Peypouquet
Publication date: 2 August 2018
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10957-018-1265-x
Convex programming (90C25) Variational inequalities (49J40) Numerical methods based on nonlinear programming (49M37)
Related Items
Sparse source identification of linear diffusion-advection equations by adjoint methods ⋮ Alternating forward-backward splitting for linearly constrained optimization problems ⋮ Unnamed Item
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Nonlinear total variation based noise removal algorithms
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- Lagrangian-penalization algorithm for constrained optimization and variational inequalities
- On the convergence of the iterates of the ``fast iterative shrinkage/thresholding algorithm
- Interior-point Lagrangian decomposition method for separable convex optimization
- Functional analysis, Sobolev spaces and partial differential equations
- Penalty-proximal methods in convex programming
- A dual algorithm for the solution of nonlinear variational problems via finite element approximation
- Produits infinis de resolvantes
- A proximal-based deomposition method for compositions method for convex minimization problems
- Image recovery via total variation minimization and related problems
- Enlargement of monotone operators with applications to variational inequalities
- A preconditioned descent algorithm for variational inequalities of the second kind involving the \(p\)-Laplacian operator
- Image denoising: learning the noise model via nonsmooth PDE-constrained optimization
- Proximal alternating directions method for structured variational inequalities
- A proximal multiplier method for separable convex minimization
- The Rate of Convergence of Nesterov's Accelerated Forward-Backward Method is Actually Faster Than $1/k^2$
- A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights
- A Generalized Forward-Backward Splitting
- Convex Optimization in Normed Spaces
- An augmented Lagrangian based parallel splitting method for separable convex minimization with applications to image processing
- Monotone Operators and the Proximal Point Algorithm
- Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
- Modified Lagrangians in convex programming and their generalizations
- Penalty/Barrier Multiplier Methods for Convex Programming Problems
- Alternating Projection-Proximal Methods for Convex Programming and Variational Inequalities
- Coupling General Penalty Schemes for Convex Programming with the Steepest Descent and the Proximal Point Algorithm
- Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems
- Convex programming in Hilbert space
- Weak convergence of the sequence of successive approximations for nonexpansive mappings
- Convex analysis and monotone operator theory in Hilbert spaces
- \(\varepsilon\)-subdifferentials in terms of subdifferentials
