Latest Articles for Convergence

Discover how deterministic chaotic maps influence the emergence of normal distributions.

The study reveals how active particles' behavior stabilizes over time through mathematical modeling.

A new method enhances stability in min-max optimization processes.

A look into the PDHG algorithm and its role in optimization methods.

Enhancing decision-making by integrating risk into reinforcement learning.

Exploring effective strategies for managing large groups of interacting agents.

A look into chattering in control and its impact on system efficiency.

A concise overview of the intersection of topology and vector spaces.

A new method utilizes deep learning for complex mathematical equations in various fields.

Investigating solutions for optimal control problems under specific constraints.

Study reveals quick paths to efficient Nash equilibria in potential games.

Improving the accuracy of numerical methods for phase separation analysis.

Introducing innovative algorithms for complex optimization challenges.

Exploring how inexact policy iteration aids decision-making in uncertain environments.

This article examines how certain Markov processes behave consistently over time.

This article discusses Domain-Inspired Sharpness-Aware Minimization for better model adaptation.

A method to enhance optimization on curved spaces with inexact calculations.

Flow matching offers a new way to generate data samples efficiently.

A method for calculating Lyapunov exponents in renewal equations to study system behavior.

This article examines two methods for solving the Schrodinger-Poisson equation in physics.

A method to solve unsymmetric saddle-point problems effectively using inexact solutions.

This article examines the theoretical aspects of the Plug-and-Play algorithm for image processing.

Improved algorithms for DC programming enhance optimization in machine learning and image processing.

Two algorithms improve decision-making for agents in competitive and cooperative environments.

This study introduces a method for solving polynomial optimization over unions of sets.

A look into cosmic shear and its influence on dark matter and energy.

Investigating the behavior and convergence of CAT-lattices within geometric structures.

A look at Particle Swarm Optimization and its applications in various fields.

A guide to multiobjective optimization techniques in machine learning and deep learning.

Learn how gravitational lensing aids our understanding of mass distribution in the universe.

An overview of applying Schwarz methods to nonlocal Dirichlet and Neumann problems.

This article examines deep linear networks and the impact of sharpness on training.

A look at how opinions form, change, and influence society.

Explore the principles and applications of stochastic approximation in uncertain environments.

A new approach improves optimization of complex loss functions in neural networks.

A look into how linear networks learn and evolve during training.

A new FFT-based method improves the study of materials with complex microstructures.

This paper explores EM algorithm behavior in mixed linear regression for improved model accuracy.

Introducing algorithms for balancing multiple objectives in optimization tasks.

A novel approach improves sampling from difficult probability distributions.