Extrapolated plug-and-play three-operator splitting methods for nonconvex optimization with applications to image restoration

Numerical mathematical programming methods (65K05) Applications of mathematical programming (90C90) Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30)

Cites Work

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Nonlinear total variation based noise removal algorithms
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
An inertial forward-backward algorithm for the minimization of the sum of two nonconvex functions
Douglas-Rachford splitting for nonconvex optimization with application to nonconvex feasibility problems
Proximal alternating linearized minimization for nonconvex and nonsmooth problems
Operator splittings, Bregman methods and frame shrinkage in image processing
A three-operator splitting scheme and its optimization applications
An inertial forward-backward algorithm for monotone inclusions
A note on the Douglas-Rachford splitting method for optimization problems involving hypoconvex functions
Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods
Inertial proximal gradient methods with Bregman regularization for a class of nonconvex optimization problems
Dualize, split, randomize: toward fast nonsmooth optimization algorithms
A survey on some recent developments of alternating direction method of multipliers
Douglas-Rachford splitting and ADMM for nonconvex optimization: accelerated and Newton-type linesearch algorithms
Convolutional proximal neural networks and plug-and-play algorithms
Convergence analysis of the generalized splitting methods for a class of nonconvex optimization problems
Asymmetric forward-backward-adjoint splitting for solving monotone inclusions involving three operators
General inertial proximal gradient method for a class of nonconvex nonsmooth optimization problems
An envelope for Davis-Yin splitting and strict saddle-point avoidance
Preconditioned three-operator splitting algorithm with applications to image restoration
Accelerated and Inexact Forward-Backward Algorithms
A Generalized Forward-Backward Splitting
iPiano: Inertial Proximal Algorithm for Nonconvex Optimization
Activity Identification and Local Linear Convergence of Forward--Backward-type Methods
Alternating Direction Algorithms for $\ell_1$-Problems in Compressive Sensing
Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Łojasiewicz Inequality
Inertial Proximal Alternating Linearized Minimization (iPALM) for Nonconvex and Nonsmooth Problems
The Split Bregman Method for L1-Regularized Problems
A General Inertial Proximal Point Algorithm for Mixed Variational Inequality Problem
Forward-Backward Envelope for the Sum of Two Nonconvex Functions: Further Properties and Nonmonotone Linesearch Algorithms
Image Restoration by Iterative Denoising and Backward Projections
Non-convex Optimization for Machine Learning
A Dynamical Approach to an Inertial Forward-Backward Algorithm for Convex Minimization
SURVEY: SIXTY YEARS OF DOUGLAS–RACHFORD
A Three-Operator Splitting Algorithm for Nonconvex Sparsity Regularization
An Operator-Splitting Method for the Gaussian Curvature Regularization Model with Applications to Surface Smoothing and Imaging
Fixed Point Strategies in Data Science
Operator Splitting Performance Estimation: Tight Contraction Factors and Optimal Parameter Selection
An Inertial Newton Algorithm for Deep Learning
Douglas--Rachford Splitting and ADMM for Nonconvex Optimization: Tight Convergence Results
Plug-and-Play Unplugged: Optimization-Free Reconstruction Using Consensus Equilibrium
Minimization of $\ell_{1-2}$ for Compressed Sensing
Convergence Analysis of Douglas--Rachford Splitting Method for “Strongly + Weakly” Convex Programming
Some methods of speeding up the convergence of iteration methods
A Bregman Forward-Backward Linesearch Algorithm for Nonconvex Composite Optimization: Superlinear Convergence to Nonisolated Local Minima
Learning Maximally Monotone Operators for Image Recovery
Proximal Splitting Algorithms for Convex Optimization: A Tour of Recent Advances, with New Twists
A generalized inertial proximal alternating linearized minimization method for nonconvex nonsmooth problems
A New Operator Splitting Method for the Euler Elastica Model for Image Smoothing

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