A continuous dynamical splitting method for solving ‘strongly+weakly’ convex programming problems
From MaRDI portal
Publication:5110327
DOI10.1080/02331934.2019.1689977zbMath1445.47050OpenAlexW2991357569MaRDI QIDQ5110327
Ming Zhu, Ya-Ping Fang, Rong Hu
Publication date: 18 May 2020
Published in: Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331934.2019.1689977
Convex programming (90C25) Numerical optimization and variational techniques (65K10) Nonsmooth analysis (49J52) Monotone operators and generalizations (47H05) Evolution inclusions (34G25) Fixed-point iterations (47J26)
Related Items (3)
Asymptotic behaviour of a nonautonomous evolution equation governed by a quasi-nonexpansive operator ⋮ A second-order adaptive Douglas-Rachford dynamic method for maximal \(\alpha\)-monotone operators ⋮ An adaptive alternating direction method of multipliers
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A dynamical system associated with the fixed points set of a nonexpansive operator
- Continuous gradient projection method in Hilbert spaces
- Semiconcave functions, Hamilton-Jacobi equations, and optimal control
- On the convergence rate of Douglas-Rachford operator splitting method
- A one-layer recurrent neural network for constrained nonconvex optimization
- On Chebyshev functions and Klee functions
- On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
- On the stability of globally projected dynamical systems
- A note on the Douglas-Rachford splitting method for optimization problems involving hypoconvex functions
- Levenberg-Marquardt dynamics associated to variational inequalities
- Peaceman-Rachford splitting for a class of nonconvex optimization problems
- Newton-like dynamics and forward-backward methods for structured monotone inclusions in Hilbert spaces
- Shadow Douglas-Rachford splitting for monotone inclusions
- Convergence rates for forward-backward dynamical systems associated with strongly monotone inclusions
- Second Order Forward-Backward Dynamical Systems For Monotone Inclusion Problems
- The Convergence Problem for Dissipative Autonomous Systems
- A Continuous Dynamical Newton-Like Approach to Solving Monotone Inclusions
- Local Linear Convergence of the ADMM/Douglas--Rachford Algorithms without Strong Convexity and Application to Statistical Imaging
- The Numerical Solution of Parabolic and Elliptic Differential Equations
- On the Numerical Solution of Heat Conduction Problems in Two and Three Space Variables
- Evolution equations with lack of convexity
- Dynamical systems and forward–backward algorithms associated with the sum of a convex subdifferential and a monotone cocoercive operator
- Implicit Functions and Solution Mappings
- Characterizations of Łojasiewicz inequalities: Subgradient flows, talweg, convexity
- From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images
- Splitting Algorithms for the Sum of Two Nonlinear Operators
- Variational Analysis
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Sparse Signal Estimation by Maximally Sparse Convex Optimization
- The Convergence Guarantees of a Non-Convex Approach for Sparse Recovery
- Day-To-Day Dynamic Network Disequilibria and Idealized Traveler Information Systems
- Adaptive Douglas--Rachford Splitting Algorithm for the Sum of Two Operators
- The Primal-Dual Hybrid Gradient Method for Semiconvex Splittings
- Convergence Analysis of Douglas--Rachford Splitting Method for “Strongly + Weakly” Convex Programming
- Nonconvex Notions of Regularity and Convergence of Fundamental Algorithms for Feasibility Problems
- A Novel Neural Network for a Class of Convex Quadratic Minimax Problems
- Convex analysis and monotone operator theory in Hilbert spaces
This page was built for publication: A continuous dynamical splitting method for solving ‘strongly+weakly’ convex programming problems