Dual descent augmented Lagrangian method and alternating direction method of multipliers

Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Optimality conditions and duality in mathematical programming (90C46)

Cites Work

Unnamed Item
Unnamed Item
Unnamed Item
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
Accelerated gradient methods for nonconvex nonlinear and stochastic programming
On the linear convergence of the alternating direction method of multipliers
A three-operator splitting scheme and its optimization applications
Monotone splitting sequential quadratic optimization algorithm with applications in electric power systems
On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
A dual algorithm for the solution of nonlinear variational problems via finite element approximation
Global convergence of unmodified 3-block ADMM for a class of convex minimization problems
A globally convergent algorithm for nonconvex optimization based on block coordinate update
Structured nonconvex and nonsmooth optimization: algorithms and iteration complexity analysis
Global convergence of ADMM in nonconvex nonsmooth optimization
Complexity of proximal augmented Lagrangian for nonconvex optimization with nonlinear equality constraints
Complexity of an inexact proximal-point penalty method for constrained smooth non-convex optimization
Moreau envelope augmented Lagrangian method for nonconvex optimization with linear constraints
A QCQP-based splitting SQP algorithm for two-block nonconvex constrained optimization problems with application
On non-ergodic convergence rate of Douglas-Rachford alternating direction method of multipliers
Perturbed proximal primal-dual algorithm for nonconvex nonsmooth optimization
Multiplier and gradient methods
The multiplier method of Hestenes and Powell applied to convex programming
Stochastic first-order methods for convex and nonconvex functional constrained optimization
A two-level distributed algorithm for nonconvex constrained optimization
A Block Coordinate Descent Method for Regularized Multiconvex Optimization with Applications to Nonnegative Tensor Factorization and Completion
On the $O(1/n)$ Convergence Rate of the Douglas–Rachford Alternating Direction Method
Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems
The Numerical Solution of Parabolic and Elliptic Differential Equations
On the Numerical Solution of Heat Conduction Problems in Two and Three Space Variables
On Augmented Lagrangian Methods with General Lower-Level Constraints
Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
On the Linear Convergence of the ADMM in Decentralized Consensus Optimization
Convergence rate bounds for a proximal ADMM with over-relaxation stepsize parameter for solving nonconvex linearly constrained problems
Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization
Penalty Dual Decomposition Method for Nonsmooth Nonconvex Optimization—Part I: Algorithms and Convergence Analysis
Penalty Dual Decomposition Method for Nonsmooth Nonconvex Optimization—Part II: Applications
A Proximal Alternating Direction Method of Multiplier for Linearly Constrained Nonconvex Minimization
Iteration-Complexity of Block-Decomposition Algorithms and the Alternating Direction Method of Multipliers
Convex Analysis
A Global Dual Error Bound and Its Application to the Analysis of Linearly Constrained Nonconvex Optimization
Iteration Complexity of an Inner Accelerated Inexact Proximal Augmented Lagrangian Method Based on the Classical Lagrangian Function
The direct extension of ADMM for multi-block convex minimization problems is not necessarily convergent
Iteration-complexity of first-order augmented Lagrangian methods for convex programming
A First-Order Primal-Dual Method for Nonconvex Constrained Optimization Based on the Augmented Lagrangian
Iteration Complexity of a Proximal Augmented Lagrangian Method for Solving Nonconvex Composite Optimization Problems with Nonlinear Convex Constraints