Cover Image

The Augmented Lagrangian Methods: Overview and Recent Advances

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Deng, Kangkang, Wang, Rui, Zhu, Zhenyuan, Zhang, Junyu, Wen, Zaiwen
Format:	Preprint
Published:	2025
Subjects:	Optimization and Control 65K05, 90C30
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Oracle complexities of augmented Lagrangian methods for nonsmooth manifold optimization
by: Deng, Kangkang, et al.
Published: (2024)

Inexact Riemannian Gradient Descent Method for Nonconvex Optimization
by: Zhou, Juan, et al.
Published: (2024)

An Augmented Lagrangian Method for Training Recurrent Neural Networks
by: Wang, Yue, et al.
Published: (2024)

Stochastic momentum ADMM for nonconvex and nonsmooth optimization with application to PnP algorithm
by: Deng, Kangkang, et al.
Published: (2025)

Augmented Lagrangian Functions for Cone Constrained Optimization: the Existence of Global Saddle Points and Exact Penalty Property
by: Dolgopolik, M. V.
Published: (2017)

Proximal methods for structured nonsmooth optimization over Riemannian submanifolds
by: Li, Qia, et al.
Published: (2024)

A cut-and-project perspective for linearized Bregman iterations
by: Dai, Yu-Hong, et al.
Published: (2024)

A Stochastic Implicit Proximal Point Algorithm for Solving Linearly Constrained Stochastic Minimax Problems
by: Zhu, Kehan, et al.
Published: (2026)

BUP-TR: Bayesian Underdetermined Projection Trust-Region Methods for Derivative-Free Optimization
by: Hu, Wei, et al.
Published: (2026)

Hybrid optimal control with mixed-integer Lagrangian methods
by: Nikitina, Viktoriya, et al.
Published: (2024)

Preconditioned Proximal Gradient Methods with Conjugate Momentum: A Subspace Perspective
by: Chen, Jian, et al.
Published: (2026)

Affordable mixed-integer Lagrangian methods: optimality conditions and convergence analysis
by: De Marchi, Alberto
Published: (2024)

Improved Penalty Function Approaches for Optimization Problems with General Orthogonality
by: Zhang, Yongshen, et al.
Published: (2026)

Proximal Gradient Descent Ascent Methods for Nonsmooth Nonconvex-Concave Minimax Problems on Riemannian Manifolds
by: Xie, Xiyuan, et al.
Published: (2025)

Nonlinear Derivative-free Constrained Optimization with a Penalty-Interior Point Method and Direct Search
by: Brilli, Andrea, et al.
Published: (2024)

The Augmented Mixing Method: Computing High-Accuracy Primal-Dual Solutions to Large-Scale SDPs via Column Updates
by: Brosch, Daniel, et al.
Published: (2025)

Parameter-Free Accelerated Quasi-Newton Method for Nonconvex Optimization
by: Marumo, Naoki
Published: (2025)

Augmented Lagrangian methods for fully convex composite optimization
by: De Marchi, Alberto, et al.
Published: (2025)

New gradient methods with 3 dimensional quadratic termination
by: Xie, Yixin, et al.
Published: (2026)

Existence of augmented Lagrange multipliers: reduction to exact penalty functions and localization principle
by: Dolgopolik, M. V.
Published: (2018)

A descent method for nonsmooth multiobjective optimization problems on Riemannian manifolds
by: Tang, Chunming, et al.
Published: (2023)

Technical results on the convergence of quasi-Newton methods for nonsmooth optimization
by: Gebken, Bennet
Published: (2025)

Stochastic optimization over proximally smooth sets
by: Davis, Damek, et al.
Published: (2020)

MATRO: Metric-Aware Trust-Region Optimization with Fully Quadratic Models
by: Hu, Wei, et al.
Published: (2026)

A New Two-dimensional Model-based Subspace Method for Large-scale Unconstrained Derivative-free Optimization: 2D-MoSub
by: Xie, Pengcheng, et al.
Published: (2023)

Riemannian Trust Region Methods for SC$^1$ Minimization
by: Zhang, Chenyu, et al.
Published: (2023)

On the asymptotic behavior of a higher-order extrapolation primal-dual interior-point method for nonlinear programming
by: Heeman, Pim, et al.
Published: (2025)

Convergence-Guaranteed Algorithms for l1/2-Regularized Quadratic Programs with Assignment Constraints
by: Xie, Lijun, et al.
Published: (2025)

An interior point method for nonlinear constrained derivative-free optimization
by: Brilli, Andrea, et al.
Published: (2021)

Stochastic Approach for Price Optimization Problems with Decision-dependent Uncertainty
by: Hikima, Yuya, et al.
Published: (2023)

Universal heavy-ball method for nonconvex optimization under Hölder continuous Hessians
by: Marumo, Naoki, et al.
Published: (2023)

An investigation of stochastic trust-region based algorithms for finite-sum minimization
by: Bellavia, Stefania, et al.
Published: (2024)

A MINRES-based Linesearch Algorithm for Nonconvex Optimization with Non-positive Curvature Detection
by: Zeng, Hanfeng, et al.
Published: (2026)

Local Convergence Analysis of ADMM for Nonconvex Composite Optimization
by: Xie, Xiyuan, et al.
Published: (2026)

Objective-Function Free Multi-Objective Optimization: Rate of Convergence and Performance of an Adagrad-like algorithm
by: De Santis, Marianna, et al.
Published: (2026)

Inexact Restoration via random models for unconstrained noisy optimization
by: Morini, Benedetta, et al.
Published: (2024)

Extragradient method with feasible inexact projection to variational inequality problem
by: Millán, R. Díaz, et al.
Published: (2023)

ASPEN: An Additional Sampling Penalty Method for Finite-Sum Optimization Problems with Nonlinear Equality Constraints
by: Krejić, Nataša, et al.
Published: (2025)

A Sequential Quadratic Programming Method for Optimization with Stochastic Objective Functions, Deterministic Inequality Constraints and Robust Subproblems
by: Qiu, Songqiang, et al.
Published: (2023)

PDFO: A Cross-Platform Package for Powell's Derivative-Free Optimization Solvers
by: Ragonneau, Tom M., et al.
Published: (2023)