Cover Image

On the Convergence of the Gradient Descent Method with Stochastic Fixed-point Rounding Errors under the Polyak-Lojasiewicz Inequality

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xia, Lu, Hochstenbach, Michiel E., Massei, Stefano
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Numerical Analysis Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Limited memory gradient methods for unconstrained optimization
by: Ferrandi, Giulia, et al.
Published: (2023)

Optimal local linear convergence of Nesterov's accelerated gradient method for $C^2$ functions under the Polyak--Łojasiewicz inequality
by: Feng, Zixu, et al.
Published: (2026)

The Essential Best and Average Rate of Convergence of the Exact Line Search Gradient Descent Method
by: Yu, Thomas
Published: (2023)

IRKA is a Riemannian Gradient Descent Method
by: Mlinarić, Petar, et al.
Published: (2023)

The Stochastic Steepest Descent Method for Robust Optimization in Banach Spaces
by: Chada, Neil K., et al.
Published: (2023)

Global Convergence and Error Propagation in Neural Gradient Flows: A Riemannian Optimization Framework
by: Zheng, Shixin, et al.
Published: (2026)

Multilevel Stochastic Gradient Descent for Optimal Control Under Uncertainty
by: Baumgarten, Niklas, et al.
Published: (2025)

Linear Convergence of the Proximal Gradient Method for Composite Optimization Under the Polyak-Łojasiewicz Inequality and Its Variant
by: Kong, Qingyuan, et al.
Published: (2024)

Genericity of Polyak-Lojasiewicz Inequalities for Entropic Mean-Field Neural ODEs
by: Daudin, Samuel, et al.
Published: (2025)

Low-Discrepancy Set Post-Processing via Gradient Descent
by: Clément, François, et al.
Published: (2025)

Convergence Analysis of Fractional Gradient Descent
by: Aggarwal, Ashwani
Published: (2023)

Inexact Projected Preconditioned Gradient Methods with Variable Metrics: General Convergence Theory via Lyapunov Approach
by: Guo, Ruchi, et al.
Published: (2025)

Gradient is All You Need? How Consensus-Based Optimization can be Interpreted as a Stochastic Relaxation of Gradient Descent
by: Riedl, Konstantin, et al.
Published: (2023)

Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares
by: Peng, Liangzu, et al.
Published: (2024)

Tight Convergence Rates in Gradient Mapping for the Difference-of-Convex Algorithm
by: Rotaru, Teodor, et al.
Published: (2025)

An Inexact General Descent Method with Applications in Differential Equation-Constrained Optimization
by: Macedo, Humberto Gimenes, et al.
Published: (2025)

Super Gradient Descent: Global Optimization requires Global Gradient
by: Achour, Seifeddine
Published: (2024)

Elliptic Reconstruction and A Posteriori Error Estimates for Parabolic Variational Inequalities
by: Antil, Harbir, et al.
Published: (2024)

Online Stochastic Gradient Methods Under Sub-Weibull Noise and the Polyak-Łojasiewicz Condition
by: Kim, Seunghyun, et al.
Published: (2021)

Properties of Fixed Points of Generalised Extra Gradient Methods Applied to Min-Max Problems
by: Farzin, Amir Ali, et al.
Published: (2025)

Interpolation-Based Gradient-Error Bounds for Use in Derivative-Free Optimization of Noisy Functions
by: Marchetti, Alejandro G., et al.
Published: (2025)

Provably Faster Gradient Descent via Long Steps
by: Grimmer, Benjamin
Published: (2023)

Error Analysis of Sampling Algorithms for Approximating Stochastic Optimal Control
by: Joshi, Anant A., et al.
Published: (2025)

Convergence Analysis for A Stochastic Maximum Principle Based Data Driven Feedback Control Algorithm
by: Liang, Siming, et al.
Published: (2024)

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

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models
by: Xu, Ziqing, et al.
Published: (2025)

Stochastic Multigrid Method for Blind Ptychographic Phase Retrieval
by: Zhang, Borong, et al.
Published: (2025)

Polyak-Lojasiewicz Inequality for Quadratically Regularized Optimal Transport
by: González-Sanz, Alberto, et al.
Published: (2026)

Adaptive Lipschitz-Free Conditional Gradient Methods for Stochastic Composite Nonconvex Optimization
by: Yuan, Ganzhao
Published: (2026)

Method of Successive Approximations for Stochastic Optimal Control: Contractivity and Convergence
by: Taoufik, Safouane, et al.
Published: (2024)

Global Convergence of High-Order Regularization Methods with Sums-of-Squares Taylor Models
by: Zhu, Wenqi, et al.
Published: (2024)

Stochastic Zeroth-Order Method for Computing Generalized Rayleigh Quotients
by: Bresch, Jonas, et al.
Published: (2025)

Gradient Descent as a Perceptron Algorithm: Understanding Dynamics and Implicit Acceleration
by: Tyurin, Alexander
Published: (2025)

Affine-Invariant Global Non-Asymptotic Convergence Analysis of BFGS under Self-Concordance
by: Jin, Qiujiang, et al.
Published: (2025)

Error Estimates of the Gain Approximation by Hermite-Galerkin Method in Feedback Particle Filter
by: Wang, Ruoyu, et al.
Published: (2026)

Projected Block Coordinate Descent for sparse spike estimation
by: Bénard, Pierre-Jean, et al.
Published: (2024)

Dual Cone Gradient Descent for Training Physics-Informed Neural Networks
by: Hwang, Youngsik, et al.
Published: (2024)

Convergence Analysis of the Upwind Difference Methods for Hamilton-Jacobi-Bellman Equations
by: Inoue, Daisuke, et al.
Published: (2023)

An Error Analysis of Second Order Elliptic Optimal Control Problem via Hybrid Higher Order Methods
by: Mallik, Gouranga, et al.
Published: (2025)

Accelerated Primal-Dual Proximal Gradient Splitting Methods for Convex-Concave Saddle-Point Problems
by: Luo, Hao
Published: (2024)