Bregman three-operator splitting methods
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Publication:2696977
DOI10.1007/s10957-022-02125-9OpenAlexW4310154446MaRDI QIDQ2696977
Lieven Vandenberghe, Xin Jiang
Publication date: 17 April 2023
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2203.00252
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- On the ergodic convergence rates of a first-order primal-dual algorithm
- A primal-dual splitting method for convex optimization involving Lipschitzian, proximable and linear composite terms
- Lectures on convex optimization
- On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
- A simplified view of first order methods for optimization
- A new primal-dual algorithm for minimizing the sum of three functions with a linear operator
- A simple algorithm for a class of nonsmooth convex-concave saddle-point problems
- A first-order primal-dual algorithm for convex problems with applications to imaging
- A splitting algorithm for dual monotone inclusions involving cocoercive operators
- Acceleration of primal-dual methods by preconditioning and simple subproblem procedures
- Bregman primal-dual first-order method and application to sparse semidefinite programming
- Dualize, split, randomize: toward fast nonsmooth optimization algorithms
- Proportional-integral projected gradient method for conic optimization
- Entropic regularization of continuous optimal transport problems
- On the equivalence of the primal-dual hybrid gradient method and Douglas-Rachford splitting
- An Inexact Hybrid Generalized Proximal Point Algorithm and Some New Results on the Theory of Bregman Functions
- CVXPY: A Python-Embedded Modeling Language for Convex Optimization
- Proximal Splitting Methods in Signal Processing
- Convergence Analysis of Primal-Dual Algorithms for a Saddle-Point Problem: From Contraction Perspective
- A General Framework for a Class of First Order Primal-Dual Algorithms for Convex Optimization in Imaging Science
- On a generalization of the iterative soft-thresholding algorithm for the case of non-separable penalty
- Convergence Analysis of a Proximal-Like Minimization Algorithm Using Bregman Functions
- Splitting Algorithms for the Sum of Two Nonlinear Operators
- First Order Methods Beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems
- First-Order Methods in Optimization
- Relatively Smooth Convex Optimization by First-Order Methods, and Applications
- A First-Order Primal-Dual Algorithm with Linesearch
- Entropic Proximal Operators for Nonnegative Trigonometric Polynomials
- Nonlinear Proximal Point Algorithms Using Bregman Functions, with Applications to Convex Programming
- A primal–dual fixed point algorithm for convex separable minimization with applications to image restoration
- A Modified Forward-Backward Splitting Method for Maximal Monotone Mappings
- A Primal-Dual Algorithm with Line Search for General Convex-Concave Saddle Point Problems
- Solving Large-Scale Optimization Problems with a Convergence Rate Independent of Grid Size
- Interior Gradient and Proximal Methods for Convex and Conic Optimization
- Proximité et dualité dans un espace hilbertien
- Convex Analysis
- A Descent Lemma Beyond Lipschitz Gradient Continuity: First-Order Methods Revisited and Applications
- An introduction to continuous optimization for imaging
