Cover Image

Multi-cut stochastic approximation methods for solving stochastic convex composite optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liang, Jiaming, Monteiro, Renato D. C., Zhang, Honghao
Format:	Preprint
Published:	2025
Subjects:	Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Proximal bundle methods for hybrid weakly convex composite optimization problems
by: Liang, Jiaming, et al.
Published: (2023)

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

Universal subgradient and proximal bundle methods for convex and strongly convex hybrid composite optimization
by: Guigues, Vincent, et al.
Published: (2024)

Bundle methods with quadratic cuts for deterministic and stochastic strongly convex optimization problems
by: Guigues, Vincent, et al.
Published: (2017)

An SDE perspective on stochastic convex optimization
by: Maulen-Soto, Rodrigo, et al.
Published: (2022)

Instance-optimal stochastic convex optimization: Can we improve upon sample-average and robust stochastic approximation?
by: Jiang, Liwei, et al.
Published: (2026)

A stochastic moving ball approximation method for smooth convex constrained minimization
by: Singh, Nitesh Kumar, et al.
Published: (2024)

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

Two-stage stochastic algorithm for solving large-scale (non)-convex separable optimization problems under affine constraints
by: Dubois-Taine, Benjamin, et al.
Published: (2026)

Primal-dual proximal bundle and conditional gradient methods for convex problems
by: Liang, Jiaming
Published: (2024)

Efficiency of stochastic coordinate proximal gradient methods on nonseparable composite optimization
by: Necoara, I., et al.
Published: (2021)

A kernel-based stochastic approximation framework for contextual optimization
by: Cao, Hao, et al.
Published: (2025)

A deep learning method for solving stochastic optimal control problems driven by fully-coupled FBSDEs
by: Ji, Shaolin, et al.
Published: (2022)

Duality methods in stochastic optimal control
by: Bank, Peter, et al.
Published: (2026)

Computer-aided analyses of stochastic first-order methods, via interpolation conditions for stochastic optimization
by: Rubbens, Anne, et al.
Published: (2025)

Mirror descent method for stochastic multi-objective optimization
by: Yang, Linxi, et al.
Published: (2024)

First-order methods for stochastic and finite-sum convex optimization with deterministic constraints
by: Lu, Zhaosong, et al.
Published: (2025)

A stochastic perturbed augmented Lagrangian method for smooth convex constrained minimization
by: Singh, Nitesh Kumar, et al.
Published: (2025)

Efficient parameter-free restarted accelerated gradient methods for convex and strongly convex optimization
by: Sujanani, Arnesh, et al.
Published: (2024)

Stochastic halfspace approximation method for convex optimization with nonsmooth functional constraints
by: Singh, Nitesh Kumar, et al.
Published: (2024)

A model reduction method based on nonlinear optimization for multiscale stochastic optimal control problems
by: Ma, Lingling, et al.
Published: (2025)

A novel L-shaped refinement chain cuts method for two-stage stochastic programs
by: Hewitt, Mike, et al.
Published: (2026)

Convergence of projected stochastic approximation algorithm
by: Borowski, Michał, et al.
Published: (2025)

A computational study of cutting-plane methods for multi-stage stochastic integer programs
by: Bansal, Akul, et al.
Published: (2024)

A stochastic gradient method for trilevel optimization
by: Giovannelli, Tommaso, et al.
Published: (2025)

A stochastic method of moving asymptotes for topology optimization under uncertainty
by: Pflug, Lukas, et al.
Published: (2024)

On adaptive stochastic heavy ball momentum for solving linear systems
by: Zeng, Yun, et al.
Published: (2023)

On the approximation error for approximating convex bodies using multiobjective optimization
by: Löhne, Andreas, et al.
Published: (2021)

Code generation for solving and differentiating through convex optimization problems
by: Schaller, Maximilian, et al.
Published: (2025)

Delayed supermartingale convergence lemmas for stochastic approximation with Nesterov momentum
by: Ming-Kun, Zhang
Published: (2024)

ICNN-enhanced 2SP: Leveraging input convex neural networks for solving two-stage stochastic programming
by: Liu, Yu, et al.
Published: (2025)

Two-norm discrepancy and convergence of the stochastic gradient method with application to shape optimization
by: Dambrine, Marc, et al.
Published: (2024)

Distributionally robust stochastic optimal control
by: Shapiro, Alexander, et al.
Published: (2024)

Stochastic smoothing accelerated gradient method for general constrained nonsmooth convex composite optimization
by: Wang, Ruyu, et al.
Published: (2023)

Convergence analysis for an implementable scheme to solve the linear-quadratic stochastic optimal control problem with stochastic wave equation
by: Chaudhary, Abhishek
Published: (2025)

Advancing the lower bounds: An accelerated, stochastic, second-order method with optimal adaptation to inexactness
by: Agafonov, Artem, et al.
Published: (2023)

Multistage stochastic optimization for drayage procurement in container logistics using stochastic dual dynamic programming
by: Vassos, Georgios, et al.
Published: (2025)

Convergence guarantees for stochastic algorithms solving non-unique problems in metric spaces
by: Pischke, Nicholas, et al.
Published: (2026)

An optimal first-order method for smooth and strongly convex composite optimization and its stationary limit
by: Upadhyaya, Manu, et al.
Published: (2026)

Near-optimal performance of stochastic economic MPC
by: Schießl, Jonas, et al.
Published: (2024)