Cover Image

Block Decomposable Methods for Large-Scale Optimization Problems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Maia, Leandro Farias
Format:	Preprint
Published:	2026
Subjects:	Optimization and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

An Inexact Weighted Proximal Trust-Region Method
by: Maia, Leandro Farias, et al.
Published: (2026)

The Randomized Block Coordinate Descent Method in the Hölder Smooth Setting
by: Maia, Leandro Farias, et al.
Published: (2024)

PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming
by: Li, Bingheng, et al.
Published: (2024)

SPO-VCS: An End-to-End Smart Predict-then-Optimize Framework with Alternating Differentiation Method for Relocation Problems in Large-Scale Vehicle Crowd Sensing
by: Wang, Xinyu, et al.
Published: (2024)

Accelerating Multi-Block Constrained Optimization Through Learning to Optimize
by: Liang, Ling, et al.
Published: (2024)

Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems
by: Garber, Dan, et al.
Published: (2022)

Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems
by: Tran-Dinh, Quoc, et al.
Published: (2023)

Interpreting Adaptive Gradient Methods by Parameter Scaling for Learning-Rate-Free Optimization
by: Suh, Min-Kook, et al.
Published: (2024)

Efficient Solving of Large Single Input Superstate Decomposable Markovian Decision Process
by: Mahjoub, Youssef Ait El, et al.
Published: (2025)

Stability of Primal-Dual Gradient Flow Dynamics for Multi-Block Convex Optimization Problems
by: Ozaslan, Ibrahim K., et al.
Published: (2024)

Penalty-Based First-Order Methods for Bilevel Optimization with Minimax and Constrained Lower-Level Problems
by: Shen, Yiyang, et al.
Published: (2026)

Learning to Shuffle: Block Reshuffling and Reversal Schemes for Stochastic Optimization
by: Nguyen, Lam M., et al.
Published: (2026)

A Composite Decomposition Method for Large-Scale Global Optimization
by: Tian, Maojiang, et al.
Published: (2024)

Inverse Optimization for Routing Problems
by: Scroccaro, Pedro Zattoni, et al.
Published: (2023)

Bayesian Optimization of Bilevel Problems
by: Ekmekcioglu, Omer, et al.
Published: (2024)

Gradient Methods with Online Scaling
by: Gao, Wenzhi, et al.
Published: (2024)

A Block Coordinate Descent Method for Nonsmooth Composite Optimization under Orthogonality Constraints
by: Yuan, Ganzhao
Published: (2023)

Fast and Large-Scale Unbalanced Optimal Transport via its Semi-Dual and Adaptive Gradient Methods
by: Genans, Ferdinand
Published: (2026)

DOVA-PATBM: An Intelligent, Adaptive, and Scalable Framework for Optimizing Large-Scale EV Charging Infrastructure
by: Li, Chuan, et al.
Published: (2025)

Bayesian Optimization for Non-Convex Two-Stage Stochastic Optimization Problems
by: Buckingham, Jack M., et al.
Published: (2024)

Primal Methods for Variational Inequality Problems with Functional Constraints
by: Zhang, Liang, et al.
Published: (2024)

Proximal Point Method for Online Saddle Point Problem
by: Meng, Qing-xin, et al.
Published: (2024)

Extragradient Type Methods for Riemannian Variational Inequality Problems
by: Hu, Zihao, et al.
Published: (2023)

Problem-Parameter-Free Decentralized Bilevel Optimization
by: Zhai, Zhiwei, et al.
Published: (2025)

Diffusion Stochastic Optimization for Min-Max Problems
by: Cai, Haoyuan, et al.
Published: (2024)

humancompatible.train: Implementing Optimization Algorithms for Stochastically-Constrained Stochastic Optimization Problems
by: Kliachkin, Andrii, et al.
Published: (2025)

A Geometric Approach to Problems in Optimization and Data Science
by: Manoj, Naren Sarayu
Published: (2025)

You Shall Pass: Dealing with the Zero-Gradient Problem in Predict and Optimize for Convex Optimization
by: Veviurko, Grigorii, et al.
Published: (2023)

Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations
by: Tyurin, Alexander, et al.
Published: (2024)

Zero-Shot Transferable Solution Method for Parametric Optimal Control Problems
by: Li, Xingjian, et al.
Published: (2025)

Surrogate-based Optimization via Clustering for Box-Constrained Problems
by: Ahmad, Maaz, et al.
Published: (2026)

Learning to Solve Optimization Problems Constrained with Partial Differential Equations
by: Guven, Yusuf, et al.
Published: (2025)

Optimality-Informed Neural Networks for Solving Parametric Optimization Problems
by: Hoffmann, Matthias K., et al.
Published: (2025)

Simultaneous Learning and Optimization via Misspecified Saddle Point Problems
by: Ahmadi, Mohammad Mahdi, et al.
Published: (2025)

Deep Distributed Optimization for Large-Scale Quadratic Programming
by: Saravanos, Augustinos D., et al.
Published: (2024)

On the Effectiveness of the z-Transform Method in Quadratic Optimization
by: Bach, Francis
Published: (2025)

On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization
by: Zhou, Dongruo, et al.
Published: (2018)

Stabilized Proximal-Point Methods for Federated Optimization
by: Jiang, Xiaowen, et al.
Published: (2024)

Gradient Methods with Online Scaling Part I. Theoretical Foundations
by: Gao, Wenzhi, et al.
Published: (2025)

Gradient Methods with Online Scaling Part II. Practical Aspects
by: Chu, Ya-Chi, et al.
Published: (2025)