Copertina

An adaptive linearized alternating direction multiplier method with a relaxation step for convex programming

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Wang, Boran
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Optimization and Control
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Accelerated linearized alternating direction method of multipliers with Nesterov extrapolation
di: He, X., et al.
Pubblicazione: (2023)

Auto-conditioned primal-dual hybrid gradient method and alternating direction method of multipliers
di: Lan, Guanghui, et al.
Pubblicazione: (2024)

On the tightness of linear relaxations of alternative mixed integer programming formulations for the generator maintenance scheduling problem
di: Andrade, Tiago
Pubblicazione: (2025)

Alternating direction method of multipliers for polynomial optimization
di: Cerone, V., et al.
Pubblicazione: (2025)

On the strength of Burer's lifted convex relaxation to quadratic programming with ball constraints
di: Kılınç-Karzan, Fatma, et al.
Pubblicazione: (2024)

The Güler-type acceleration for proximal gradient, linearized augmented Lagrangian and linearized alternating direction method of multipliers
di: Zhou, Bin, et al.
Pubblicazione: (2025)

An over-relaxed ADMM for separable convex programming and its applications to statistical learning
di: Ni, Renyuan
Pubblicazione: (2024)

Reinforcement learning for adaptive interior point methods in convex quadratic programming
di: Bertoncini, Jeremy, et al.
Pubblicazione: (2025)

Lagrange multiplier expressions for matrix polynomial optimization and tight relaxations
di: Huang, Lei, et al.
Pubblicazione: (2025)

On moment relaxations for linear state feedback controller synthesis with non-convex quadratic costs and constraints
di: Gramlich, Dennis, et al.
Pubblicazione: (2024)

Pseudo basic steps: Bound improvement guarantees from Lagrangian decomposition in convex disjunctive programming
di: Papageorgiou, Dimitri J., et al.
Pubblicazione: (2025)

A matrix-free interior point continuous trajectory for linearly constrained convex programming
di: Qian, Xun, et al.
Pubblicazione: (2024)

Convergence towards a local minimum by direct search methods with a covering step
di: Audet, Charles, et al.
Pubblicazione: (2024)

On the facet pivot simplex method for linear programming II: a linear iteration bound
di: Yang, Yaguang
Pubblicazione: (2022)

A hierarchy of convex relaxations for the total variation distance
di: Lasserre, Jean-Bernard
Pubblicazione: (2024)

On semidefinite descriptions for convex hulls of quadratic programs
di: Wang, Alex L., et al.
Pubblicazione: (2024)

Tight semidefinite programming relaxations for sparse box-constrained quadratic programs
di: Khajavirad, Aida
Pubblicazione: (2026)

Research on the descent direction of prediction correction algorithms for pseudo-convex/convex optimization problems
di: Li, Ting, et al.
Pubblicazione: (2025)

An adaptive proximal safeguarded augmented Lagrangian method for nonsmooth DC problems with convex constraints
di: Kanzow, Christian, et al.
Pubblicazione: (2025)

From quantum to quantum-inspired: the LogQ algorithm as a non-linear continuous relaxation of variables method
di: Messud, Jérémie, et al.
Pubblicazione: (2026)

Parameter-free proximal bundle methods with adaptive stepsizes for hybrid convex composite optimization problems
di: Monteiro, Renato D. C., et al.
Pubblicazione: (2024)

On the integrality gap of convex mixed-integer programs
di: Kocuk, Burak, et al.
Pubblicazione: (2024)

Learning a convex cost-to-go for single step model predictive control
di: Turan, E. M., et al.
Pubblicazione: (2023)

Distributed alternating gradient descent for convex semi-infinite programs over a network
di: Aravind, Ashwin, et al.
Pubblicazione: (2024)

First-order SDSOS-convex semi-algebraic optimization and exact SOCP relaxations
di: Yang, Chengmiao, et al.
Pubblicazione: (2025)

Semidefinite relaxations for nonlinear elasticity with energies convex in the Cauchy-Green strain tensor
di: Henrion, Didier, et al.
Pubblicazione: (2026)

Numerical analysis of the convex relaxation of the barrier parameter functional of self-concordant barriers
di: Pirau, Vitali, et al.
Pubblicazione: (2025)

On the optimal pivot path of simplex method for linear programming based on reinforcement learning
di: Li, Anqi, et al.
Pubblicazione: (2022)

A unified framework for inexact adaptive stepsizes in the gradient methods, the conjugate gradient methods and the quasi-Newton methods for strictly convex quadratic optimization
di: Liu, Zexian
Pubblicazione: (2026)

A New Fast Adaptive Linearized Alternating Direction Multiplier Method for Convex Optimization
di: Wang, Boran
Pubblicazione: (2024)

Tightening convex relaxations of trained neural networks: a unified approach for convex and S-shaped activations
di: Carrasco, Pablo, et al.
Pubblicazione: (2024)

An accelerated gradient method with adaptive restart for convex multiobjective optimization problems
di: Luo, Hao, et al.
Pubblicazione: (2025)

Instance-specific linear relaxations of semidefinite optimization problems
di: de Roux, Daniel, et al.
Pubblicazione: (2023)

Dynamic programming and dimensionality in convex stochastic optimization and control
di: Pennanen, Teemu, et al.
Pubblicazione: (2025)

Error bounds, PL condition, and quadratic growth for weakly convex functions, and linear convergences of proximal point methods
di: Liao, Feng-Yi, et al.
Pubblicazione: (2023)

Empirical and computer-aided robustness analysis of long-step and accelerated methods in smooth convex optimization
di: Vernimmen, Pierre, et al.
Pubblicazione: (2025)

Stochastic dual coordinate descent with adaptive heavy ball momentum for linearly constrained convex optimization
di: Zeng, Yun, et al.
Pubblicazione: (2023)

Scholtes relaxation method for pessimistic bilevel optimization
di: Benchouk, Imane, et al.
Pubblicazione: (2021)

Computing AD-compatible subgradients of convex relaxations of implicit functions
di: Song, Yingkai, et al.
Pubblicazione: (2025)

Balancing adaptability and predictability: K-revision multistage stochastic programming
di: Wang, Chengwenjian, et al.
Pubblicazione: (2026)