Cover Image

A Dual Method for Minimax Quadratic Programming

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ren, Wenhui, Zhang, Liwei
Format:	Preprint
Published:	2025
Subjects:	Optimization and Control 90C20, 90C47, 65K05
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Line-search and Adaptive Step Sizes for Nonconvex-strongly-concave Minimax Optimization
by: Ma, Bohao, et al.
Published: (2026)

Time-integrated Optimal Transport: A Robust Minimax Framework
by: Nguyen, Thai P. D., et al.
Published: (2025)

A Vectorized Positive Semidefinite Penalty Method for Unconstrained Binary Quadratic Programming
by: Huo, Xinyue, et al.
Published: (2024)

Optimality Conditions and Numerical Algorithms for a Class of Minimax Bilevel Optimization Problems
by: Hu, Yaling, et al.
Published: (2026)

A Random Active Set Method for Strictly Convex Quadratic Problem with Simple Bounds
by: Gu, Ran, et al.
Published: (2021)

Bounding-Focused Discretization Methods for the Global Optimization of Nonconvex Semi-Infinite Programs
by: Turan, Evren M., et al.
Published: (2023)

Symplectic Extra-gradient Type Method for Solving General Non-monotone Inclusion Problem
by: Yuan, Ya-xiang, et al.
Published: (2024)

Symplectic Discretization Approach for Developing New Proximal Point Algorithm
by: Yuan, Ya-xiang, et al.
Published: (2023)

Splitting Algorithms for Distributionally Robust Optimization
by: Briceño-Arias, Luis, et al.
Published: (2024)

Strong Convergence of FISTA for Affinely Constrained Convex Quadratic Minimization
by: Bartz, Sedi, et al.
Published: (2026)

Fast Optimistic Gradient Descent Ascent (OGDA) method in continuous and discrete time
by: Bot, Radu Ioan, et al.
Published: (2022)

A Sequential Quadratic Programming Method for Optimization with Stochastic Objective Functions, Deterministic Inequality Constraints and Robust Subproblems
by: Qiu, Songqiang, et al.
Published: (2023)

Proximal Gradient Descent Ascent Methods for Nonsmooth Nonconvex-Concave Minimax Problems on Riemannian Manifolds
by: Xie, Xiyuan, et al.
Published: (2025)

Difference of Convex (DC) approach for neural network approximation with uniform loss function
by: Peiris, Vinesha, et al.
Published: (2026)

Convergence-Guaranteed Algorithms for l1/2-Regularized Quadratic Programs with Assignment Constraints
by: Xie, Lijun, et al.
Published: (2025)

Active set identification and rapid convergence for degenerate primal-dual problems
by: Díaz, Mateo, et al.
Published: (2026)

$Q$-fully Quadratic Modeling and its Application in a Random Subspace Derivative-free Method
by: Chen, Yiwen, et al.
Published: (2023)

Forward Primal-Dual Half-Forward Algorithm for Splitting Four Operators
by: Roldán, Fernando
Published: (2023)

Inexact Riemannian Gradient Descent Method for Nonconvex Optimization
by: Zhou, Juan, et al.
Published: (2024)

Distributed accelerated proximal conjugate gradient methods for multi-agent constrained optimization problems
by: Gebrie, Anteneh Getachew
Published: (2023)

MATRO: Metric-Aware Trust-Region Optimization with Fully Quadratic Models
by: Hu, Wei, et al.
Published: (2026)

On the convergence of adaptive first order methods: proximal gradient and alternating minimization algorithms
by: Latafat, Puya, et al.
Published: (2023)

Adaptive proximal gradient methods are universal without approximation
by: Oikonomidis, Konstantinos A., et al.
Published: (2024)

Adaptive proximal algorithms for convex optimization under local Lipschitz continuity of the gradient
by: Latafat, Puya, et al.
Published: (2023)

Tikhonov regularization of monotone operator flows not only ensures strong convergence of the trajectories but also speeds up the vanishing of the residuals
by: Bot, Radu Ioan, et al.
Published: (2024)

A Three-Operator Splitting Scheme Derived from Three-Block ADMM
by: Anshika, Anshika, et al.
Published: (2024)

On Solution Uniqueness and Robust Recovery for Sparse Regularization with a Gauge: from Dual Point of View
by: He, Jiahuan, et al.
Published: (2023)

An Algorithm to Solve Cardinality Constrained Quadratic Optimization Problem with an Application to the Best Subset Selection in Regression
by: Singh, Vikram, et al.
Published: (2025)

Identification of Active Subfunctions in Finite-Max Minimisation via a Smooth Reformulation
by: Ras, Charl, et al.
Published: (2024)

The Augmented Mixing Method: Computing High-Accuracy Primal-Dual Solutions to Large-Scale SDPs via Column Updates
by: Brosch, Daniel, et al.
Published: (2025)

A New Two-dimensional Model-based Subspace Method for Large-scale Unconstrained Derivative-free Optimization: 2D-MoSub
by: Xie, Pengcheng, et al.
Published: (2023)

On the Relationships among GPU-Accelerated First-Order Methods for Solving Linear Programming
by: Chen, Kaihuang, et al.
Published: (2025)

Parameter-Free Accelerated Quasi-Newton Method for Nonconvex Optimization
by: Marumo, Naoki
Published: (2025)

Relaxed and inertial nonlinear Forward-Backward algorithm
by: Maulén, Juan José, et al.
Published: (2025)

Relaxed and Inertial Nonlinear Forward-Backward with Momentum
by: Roldán, Fernando, et al.
Published: (2024)

Trust-Region Method for Optimization of Set-Valued Maps Given by Finitely Many Functions
by: Ghosh, Suprova, et al.
Published: (2025)

A Massively Parallel Interior-Point Method for Arrowhead Linear Programs with Local Linking Structure
by: Kempke, Nils-Christian, et al.
Published: (2024)

A Stochastic Implicit Proximal Point Algorithm for Solving Linearly Constrained Stochastic Minimax Problems
by: Zhu, Kehan, et al.
Published: (2026)

A first-order augmented Lagrangian method for constrained minimax optimization
by: Lu, Zhaosong, et al.
Published: (2023)

A first-order method for nonconvex-strongly-concave constrained minimax optimization
by: Lu, Zhaosong, et al.
Published: (2025)