Fast Augmented Lagrangian Method in the convex regime with convergence guarantees for the iterates. [PDF]
Math Program, 2023 This work aims to minimize a continuously differentiable convex function with Lipschitz continuous gradient under linear equality constraints. The proposed inertial algorithm results from the discretization of the second-order primal-dual dynamical ...
Boţ RI, Csetnek ER, Nguyen DK.
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Pareto front approximation through a multi-objective augmented Lagrangian method
EURO Journal on Computational Optimization, 2021 In this manuscript, we consider smooth multi-objective optimization problems with convex constraints. We propose an extension of a multi-objective augmented Lagrangian Method from recent literature.
Guido Cocchi +2 more
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An Efficient Augmented Lagrangian Method for Statistical X-Ray CT Image Reconstruction. [PDF]
PLoS ONE, 2015 Statistical iterative reconstruction (SIR) for X-ray computed tomography (CT) under the penalized weighted least-squares criteria can yield significant gains over conventional analytical reconstruction from the noisy measurement.
Jiaojiao Li +8 more
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FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret. [PDF]
Comput Vis ECCV, 2020 Algorithmic decision making based on computer vision and machine learning methods continues to permeate our lives. But issues related to biases of these models and the extent to which they treat certain segments of the population unfairly, have led to ...
Lokhande VS, Akash AK, Ravi SN, Singh V.
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An accelerated proximal augmented Lagrangian method and its application in compressive sensing [PDF]
Journal of Inequalities and Applications, 2017 As a first-order method, the augmented Lagrangian method (ALM) is a benchmark solver for linearly constrained convex programming, and in practice some semi-definite proximal terms are often added to its primal variable’s subproblem to make it more ...
Min Sun, Jing Liu
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An augmented Lagrangian method for optimization problems with structured geometric constraints [PDF]
Mathematical programming, 2021 This paper is devoted to the theoretical and numerical investigation of an augmented Lagrangian method for the solution of optimization problems with geometric constraints.
Xiao-Yao Jia +3 more
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The Augmented Lagrangian Method as a Framework for Stabilised Methods in Computational Mechanics [PDF]
Archives of Computational Methods in Engineering, 2022 In this paper we will present a review of recent advances in the application of the augmented Lagrange multiplier method as a general approach for generating multiplier-free stabilised methods.
E. Burman, P. Hansbo, M. Larson
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Constraint Qualifications and Strong Global Convergence Properties of an Augmented Lagrangian Method on Riemannian Manifolds [PDF]
SIAM Journal on Optimization, 2023 In the past years, augmented Lagrangian methods have been successfully applied to several classes of non-convex optimization problems, inspiring new developments in both theory and practice.
R. Andreani +3 more
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Stochastic inexact augmented Lagrangian method for nonconvex expectation constrained optimization [PDF]
Computational optimization and applications, 2022 Many real-world problems not only have complicated nonconvex functional constraints but also use a large number of data points. This motivates the design of efficient stochastic methods on finite-sum or expectation constrained problems. In this paper, we
Zichong Li +4 more
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Moreau Envelope Augmented Lagrangian Method for Nonconvex Optimization with Linear Constraints [PDF]
Journal of Scientific Computing, 2021 The augmented Lagrangian method (ALM) is one of the most useful methods for constrained optimization. Its convergence has been well established under convexity assumptions or smoothness assumptions, or under both assumptions.
Jinshan Zeng, W. Yin, Ding-Xuan Zhou
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