Image de couverture de livre

General Optimal Step-size for ADMM-type Algorithms: Domain Parametrization and Optimal Rates

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Ran, Yifan
Format:	Preprint
Publié:	2023
Sujets:	Optimization and Control 90C25, 90C06, 65K05, 65F22
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Monomial barrier functions for the box-constrained convex optimization problems
par: Fayed, Hatem
Publié: (2024)

Fast Frank--Wolfe Algorithms with Adaptive Bregman Step-Size for Weakly Convex Functions
par: Takahashi, Shota, et autres
Publié: (2025)

Bregman Stochastic Proximal Point Algorithm with Variance Reduction
par: Traoré, Cheik, et autres
Publié: (2025)

Simplex Frank-Wolfe: Linear Convergence and Its Numerical Efficiency for Convex Optimization over Polytopes
par: Wang, Haoning, et autres
Publié: (2025)

An efficient second-order cone programming approach for dynamic optimal transport on staggered grid discretization
par: Chen, Liang, et autres
Publié: (2025)

Performance Estimation for Smooth and Strongly Convex Sets
par: Luner, Alan, et autres
Publié: (2024)

On Averaging and Extrapolation for Gradient Descent
par: Luner, Alan, et autres
Publié: (2024)

On the convergence of proximal gradient methods for convex simple bilevel optimization
par: Latafat, Puya, et autres
Publié: (2023)

The Global R-linear Convergence of Nesterov's Accelerated Gradient Method with Unknown Strongly Convex Parameter
par: Bao, Chenglong, et autres
Publié: (2023)

Accelerated Gradient Methods with Gradient Restart: Global Linear Convergence
par: Bao, Chenglong, et autres
Publié: (2024)

Line-search and Adaptive Step Sizes for Nonconvex-strongly-concave Minimax Optimization
par: Ma, Bohao, et autres
Publié: (2026)

Active set identification and rapid convergence for degenerate primal-dual problems
par: Díaz, Mateo, et autres
Publié: (2026)

A Massively Parallel Interior-Point Method for Arrowhead Linear Programs with Local Linking Structure
par: Kempke, Nils-Christian, et autres
Publié: (2024)

A Single-Loop Stochastic Proximal Quasi-Newton Method for Large-Scale Nonsmooth Convex Optimization
par: Song, Yongcun, et autres
Publié: (2024)

A structured L-BFGS method and its application to inverse problems
par: Mannel, Florian, et autres
Publié: (2023)

A structured L-BFGS method with diagonal scaling and its application to image registration
par: Mannel, Florian, et autres
Publié: (2024)

A Random Active Set Method for Strictly Convex Quadratic Problem with Simple Bounds
par: Gu, Ran, et autres
Publié: (2021)

A MINRES-based Linesearch Algorithm for Nonconvex Optimization with Non-positive Curvature Detection
par: Zeng, Hanfeng, et autres
Publié: (2026)

Anderson Accelerated Primal-Dual Hybrid Gradient for solving LP
par: Zhou, Yingxin, et autres
Publié: (2025)

Semi-Monotone Goldstein Line Search Strategy with Application in Sparse Recovery
par: Shabani, Shima, et autres
Publié: (2025)

On the Convergence Rates of Iterative Regularization Algorithms for Composite Bi-Level Optimization
par: Shtern, Shimrit, et autres
Publié: (2025)

A linesearch-type normal map-based semismooth Newton method for nonsmooth nonconvex composite optimization
par: Zeng, Hanfeng, et autres
Publié: (2026)

$Q$-fully Quadratic Modeling and its Application in a Random Subspace Derivative-free Method
par: Chen, Yiwen, et autres
Publié: (2023)

On a globally convergent semismooth* Newton method in nonsmooth nonconvex optimization
par: Gfrerer, H.
Publié: (2024)

CLARSTA: A random subspace trust-region algorithm for convex-constrained derivative-free optimization
par: Chen, Yiwen, et autres
Publié: (2025)

Oracle complexities of augmented Lagrangian methods for nonsmooth manifold optimization
par: Deng, Kangkang, et autres
Publié: (2024)

A Three-Operator Splitting Scheme Derived from Three-Block ADMM
par: Anshika, Anshika, et autres
Publié: (2024)

Linesearch-free adaptive Bregman proximal gradient for convex minimization without relative smoothness
par: Ou, Hongjia, et autres
Publié: (2025)

Nonsmooth Projection-Free Optimization with Functional Constraints
par: Asgari, Kamiar, et autres
Publié: (2023)

On the convergence of adaptive first order methods: proximal gradient and alternating minimization algorithms
par: Latafat, Puya, et autres
Publié: (2023)

Adaptive proximal algorithms for convex optimization under local Lipschitz continuity of the gradient
par: Latafat, Puya, et autres
Publié: (2023)

Adaptive proximal gradient methods are universal without approximation
par: Oikonomidis, Konstantinos A., et autres
Publié: (2024)

Safeguarding adaptive methods: global convergence of Barzilai-Borwein and other stepsize choices
par: Ou, Hongjia, et autres
Publié: (2024)

On Solution Uniqueness and Robust Recovery for Sparse Regularization with a Gauge: from Dual Point of View
par: He, Jiahuan, et autres
Publié: (2023)

Stochastic momentum ADMM for nonconvex and nonsmooth optimization with application to PnP algorithm
par: Deng, Kangkang, et autres
Publié: (2025)

Extragradient method with feasible inexact projection to variational inequality problem
par: Millán, R. Díaz, et autres
Publié: (2023)

Preconditioned Proximal Gradient Methods with Conjugate Momentum: A Subspace Perspective
par: Chen, Jian, et autres
Publié: (2026)

Lipschitz continuity of solution multifunctions of extended $\ell_1$ regularization problems
par: Meng, Kaiwen, et autres
Publié: (2024)

A Regression-Based Prediction-Correction Method for Stochastic Time-Varying Optimization Problems
par: Kamijima, Tomoya, et autres
Publié: (2025)

Stochastic Block Bregman Projection with Polyak-like Stepsize for Possibly Inconsistent Convex Feasibility Problems
par: Zhang, Lu, et autres
Publié: (2026)