Cover Image

A Symplectic Discretization Based Proximal Point Algorithm for Convex Minimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yuan, Ya-xiang, Zhang, Yi
Format:	Preprint
Published:	2024
Subjects:	Optimization and Control 49J52, 65B99, 65K10, 65K15, 68Q25, 90C25, 90C26
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Minimization Over the Nonconvex Sparsity Constraint Using A Hybrid First-order method
by: Yang, Xiangyu, et al.
Published: (2021)

Error Bounds for a Class of Cone-Convex Inclusion Problems
by: Huy, Nguyen Quang, et al.
Published: (2025)

Quasar-Convex Optimization: Fundamental Properties and High-Order Proximal-Point Methods
by: Ahookhosh, Masoud, et al.
Published: (2026)

An inertial iteratively regularized extragradient method for bilevel variational inequality problems
by: Alves, M. Marques, et al.
Published: (2025)

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

ItsOPT: An inexact two-level smoothing framework for nonconvex optimization via high-order Moreau envelope
by: Kabgani, Alireza, et al.
Published: (2024)

ItsDEAL: Inexact two-level smoothing descent algorithms for weakly convex optimization
by: Kabgani, Alireza, et al.
Published: (2025)

A Proximal-Gradient Method for Constrained Optimization
by: Dai, Yutong, et al.
Published: (2024)

On circumcentered direct methods for monotone variational inequality problems
by: Behling, Roger, et al.
Published: (2025)

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

Convergence of the Preconditioned Proximal Point Method and Douglas-Rachford Splitting in the Absence of Monotonicity
by: Evens, Brecht, et al.
Published: (2023)

A Proximal-Gradient Method for Solving Regularized Optimization Problems with General Constraints
by: Curtis, Frank E., et al.
Published: (2025)

Shadow splitting methods for nonconvex optimisation: epi-approximation, convergence and saddle point avoidance
by: Atenas, Felipe
Published: (2025)

Understanding the Douglas-Rachford splitting method through the lenses of Moreau-type envelopes
by: Atenas, Felipe
Published: (2023)

Nonsmooth Projection-Free Optimization with Functional Constraints
by: Asgari, Kamiar, et al.
Published: (2023)

Strong Convergence of Relaxed Inertial Inexact Progressive Hedging Algorithm for Multi-stage Stochastic Variational Inequality Problems
by: Chen, Jiaxin, et al.
Published: (2024)

MGProx: A nonsmooth multigrid proximal gradient method with adaptive restriction for strongly convex optimization
by: Ang, Andersen, et al.
Published: (2023)

Fast Reflected Forward-Backward algorithm: achieving fast convergence rates for convex optimization with linear cone constraints
by: Bot, Radu Ioan, et al.
Published: (2024)

Riemannian Trust Region Methods for SC$^1$ Minimization
by: Zhang, Chenyu, et al.
Published: (2023)

Parallel Polyhedral Projection Method for the Convex Feasibility Problem
by: Barros, Pablo, et al.
Published: (2025)

Nonsmooth Convex Optimization using the Specular Gradient Method with Root-Linear Convergence
by: Jung, Kiyuob, et al.
Published: (2024)

The Golden Ratio Proximal ADMM with Norm Independent Step-Sizes for Separable Convex Optimization
by: Soe, Santanu, et al.
Published: (2025)

A finitely convergent circumcenter method for the Convex Feasibility Problem
by: Behling, Roger, et al.
Published: (2023)

Convergence of iterates and improved rates for accelerated augmented Lagrangian methods for linearly constrained convex optimization
by: He, Xin, et al.
Published: (2026)

A relaxed version of Ryu's three-operator splitting method for structured nonconvex optimization
by: Alcantara, Jan Harold, et al.
Published: (2025)

Riemannian Adaptive Regularized Newton Methods with Hölder Continuous Hessians
by: Zhang, Chenyu, et al.
Published: (2023)

Bregman Stochastic Proximal Point Algorithm with Variance Reduction
by: Traoré, Cheik, et al.
Published: (2025)

On the Convergence Rates of Iterative Regularization Algorithms for Composite Bi-Level Optimization
by: Shtern, Shimrit, et al.
Published: (2025)

An adaptive framework for first-order gradient methods
by: Hu, Xiaozhe, et al.
Published: (2026)

An Inexact Boosted Difference of Convex Algorithm for Nondifferentiable Functions
by: Ferreira, Orizon P., et al.
Published: (2024)

A Proximal Stochastic Gradient Method with Adaptive Step Size and Variance Reduction for Convex Composite Optimization
by: Fang, Changjie, et al.
Published: (2025)

The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization
by: Bergmann, Ronny, et al.
Published: (2025)

Optimization in Theory and Practice
by: Wright, Stephen J.
Published: (2025)

A preconditioned difference of convex functions algorithm with extrapolation and line search
by: Zhang, Ran, et al.
Published: (2025)

A truncated epsilon-subdifferential method for global DC optimization
by: Bagirov, Adil M., et al.
Published: (2025)

Subgradient Regularization: A Descent-Oriented Subgradient Method for Nonsmooth Optimization
by: Li, Hanyang, et al.
Published: (2025)

Inexact Limited Memory Bundle Method
by: Lampainen, Jenni, et al.
Published: (2026)

Moreau envelope and proximal-point methods under the lens of high-order regularization
by: Kabgani, Alireza, et al.
Published: (2025)

Stochastic Inertial Dynamics Via Time Scaling and Averaging
by: Maulen-Soto, Rodrigo, et al.
Published: (2024)