Latest Articles for Convergence

This article examines key mathematical spaces and their interrelations.

A look at the significance of random variables and empirical measures in probability.

Research reveals how delays hinder algorithms in min-max optimization tasks.

Weak lensing reveals the distribution of matter in the universe through galaxy distortion.

An insight into how shape stability impacts mathematical problems.

This article discusses managing communication noise in federated learning for better model performance.

New algorithms improve control for complex systems like hypersonic vehicles.

A method to solve block lower triangular Toeplitz systems efficiently using preconditioned MINRES.

An overview of two methods for solving linear equations.

Learn about subgradient methods and their role in minimizing convex functions.

This article explores the complexities of multi-agent learning and its impact on stability.

A closer look at softmax-ReLU regression and its impact on language models.

Exploring the estimation of the Hardy constant using finite element methods.

Explore the significance and properties of SRB measures in chaotic systems.

Learn how approximation theory simplifies complex functions for practical applications.

Explore how limits and matrix theory connect to real semisimple Lie groups.

A look at cancellation properties in probabilistic systems and their implications.

This article explores oscillatory solutions and their connections to periodic solutions in delay differential equations.

This research presents a novel algorithm for estimating parameters in hybrid systems.

A new method streamlines calculations for studying electron behavior in complex molecules.

A look at smoothing techniques for optimizing challenging nonsmooth functions.

A new method for approximating functions with singularities, ensuring accuracy and flexibility.

An overview of key concepts in mathematical surfaces and their functions.

Learn how scientists solve complex linear systems in plasma physics research.

Learn how to manage delays in gradient descent effectively.

New methods enhance image quality through optimization and advanced noise reduction.

New techniques improve solving Helmholtz equations in various fields.

A new approach to tackle complex composite optimization problems effectively.

Learn how preconditioning enhances optimization methods for faster solutions.

Explore the fascinating connections between Hindman spaces, ideals, and convergence.

A look at variational inequalities and the extragradient method for efficient problem-solving.

This article explores how symmetries impact the learning behavior of neural networks.

Introducing an improved method for optimization in machine learning.

Introducing a method to optimize functions with inexact gradients and Hessians.

An overview of issues in training neural networks using non-differentiable loss functions.

A study on rare events, convergence, and feedback control in nanoparticle systems.

New methods improve smoothness in curves despite noisy data challenges.

A method for optimization with multiple functions and constraints, widely applicable in various fields.

This paper discusses enhancing stochastic optimization through recurrent data sampling and regularization methods.

A new method enhances simulation speed and accuracy across various scientific fields.