Image de couverture de livre

Essential Convergence Rates of Continuous-Time Models for Optimization Methods

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ushiyama, Kansei, Sato, Shun, Matsuo, Takayasu
Format:	Preprint
Publié:	2025
Sujets:	Optimization and Control 65K05, 90C25, 65L20
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Accelerating Diagonal Methods for Bilevel Optimization: Unified Convergence via Continuous-Time Dynamics
par: Boţ, Radu Ioan, et autres
Publié: (2025)

A novel interpretation of Nesterov's acceleration via variable step-size linear multistep methods
par: Nozawa, Ryota, et autres
Publié: (2024)

A Random Active Set Method for Strictly Convex Quadratic Problem with Simple Bounds
par: Gu, Ran, et autres
Publié: (2021)

On the Convergence Rates of Iterative Regularization Algorithms for Composite Bi-Level Optimization
par: Shtern, Shimrit, et autres
Publié: (2025)

Multi-Iteration Stochastic Optimizers
par: Carlon, Andre, et autres
Publié: (2020)

A Regression-Based Prediction-Correction Method for Stochastic Time-Varying Optimization Problems
par: Kamijima, Tomoya, et autres
Publié: (2025)

BISTRO -- A Bi-Fidelity Stochastic Gradient Framework using Trust-Regions for Optimization Under Uncertainty
par: Dixon, Thomas O., et autres
Publié: (2025)

Simplex Frank-Wolfe: Linear Convergence and Its Numerical Efficiency for Convex Optimization over Polytopes
par: Wang, Haoning, et autres
Publié: (2025)

Dynamic FISTA for Convex Composite Bi-Level Optimization
par: Merchav, Roey, et autres
Publié: (2024)

Deep Centralization for the Circumcentered Reflection Method
par: Barros, Pablo
Publié: (2025)

Accelerated Gradient Methods with Gradient Restart: Global Linear Convergence
par: Bao, Chenglong, et autres
Publié: (2024)

A Proximal-Gradient Method for Constrained Optimization
par: Dai, Yutong, et autres
Publié: (2024)

General Optimal Step-size for ADMM-type Algorithms: Domain Parametrization and Optimal Rates
par: Ran, Yifan
Publié: (2023)

Monomial barrier functions for the box-constrained convex optimization problems
par: Fayed, Hatem
Publié: (2024)

Accelerated optimization algorithms and ordinary differential equations: the convex non Euclidean case
par: Dobson, Paul, et autres
Publié: (2024)

A Proximal-Gradient Method for Solving Regularized Optimization Problems with General Constraints
par: Curtis, Frank E., et autres
Publié: (2025)

The Global R-linear Convergence of Nesterov's Accelerated Gradient Method with Unknown Strongly Convex Parameter
par: Bao, Chenglong, et autres
Publié: (2023)

Nonsmooth Projection-Free Optimization with Functional Constraints
par: Asgari, Kamiar, et autres
Publié: (2023)

Preconditioned Proximal Gradient Methods with Conjugate Momentum: A Subspace Perspective
par: Chen, Jian, et autres
Publié: (2026)

Bregman proximal gradient method for linear optimization under entropic constraints
par: Briceño-Arias, Luis M., et autres
Publié: (2025)

A Dual Method for Minimax Quadratic Programming
par: Ren, Wenhui, et autres
Publié: (2025)

Convergence Rates for $\ell_p$ Norm Minimization in Convex Vector Optimization
par: Alshahrani, Mohammed
Publié: (2026)

Optimization in Theory and Practice
par: Wright, Stephen J.
Publié: (2025)

Inexact Riemannian Gradient Descent Method for Nonconvex Optimization
par: Zhou, Juan, et autres
Publié: (2024)

A Vectorized Positive Semidefinite Penalty Method for Unconstrained Binary Quadratic Programming
par: Huo, Xinyue, et autres
Publié: (2024)

Relaxed and inertial nonlinear Forward-Backward algorithm
par: Maulén, Juan José, et autres
Publié: (2025)

Preconditioned primal-dual dynamics in convex optimization: non-ergodic convergence rates
par: Apidopoulos, Vassilis, et autres
Publié: (2025)

A Three-Operator Splitting Scheme Derived from Three-Block ADMM
par: Anshika, Anshika, et autres
Publié: (2024)

Relaxed and Inertial Nonlinear Forward-Backward with Momentum
par: Roldán, Fernando, et autres
Publié: (2024)

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

Lipschitz continuity of solution multifunctions of extended $\ell_1$ regularization problems
par: Meng, Kaiwen, et autres
Publié: (2024)

Performance Estimation for Smooth and Strongly Convex Sets
par: Luner, Alan, et autres
Publié: (2024)

Stochastic Block Bregman Projection with Polyak-like Stepsize for Possibly Inconsistent Convex Feasibility Problems
par: Zhang, Lu, et autres
Publié: (2026)

On Averaging and Extrapolation for Gradient Descent
par: Luner, Alan, et autres
Publié: (2024)

Extragradient method with feasible inexact projection to variational inequality problem
par: Millán, R. Díaz, et autres
Publié: (2023)

Strong Convergence of Relaxed Inertial Inexact Progressive Hedging Algorithm for Multi-stage Stochastic Variational Inequality Problems
par: Chen, Jiaxin, et autres
Publié: (2024)

Local Convergence of Adaptively Regularized Tensor Methods
par: Welzel, Karl, et autres
Publié: (2025)

Objective-Function Free Multi-Objective Optimization: Rate of Convergence and Performance of an Adagrad-like algorithm
par: De Santis, Marianna, et autres
Publié: (2026)

Adaptive Multilevel Newton: A Quadratically Convergent Optimization Method
par: Tsipinakis, Nick, et autres
Publié: (2025)

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