Latest Articles for Convergence

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.

Examining how dark matter and energy influence cosmic structures via gravitational lensing.

Introducing new algorithms for efficient bilevel optimization in machine learning.

A new method improves decision-making under uncertainty using robust Markov Decision Processes.

This article discusses adaptive MCMC methods and their applications in complex distributions.

A look at the arc-search interior-point algorithm and its applications.

Examining quantization techniques for better distributed learning across various network structures.

Learn how step size affects gradient descent in logistic regression.

Examining the dynamics of ferromagnetic materials through advanced modeling techniques.

A study of power series solutions and their applications across various fields.

A look at how empirical processes help analyze data in various fields.

A new method enhances LoRA efficiency and performance in training large models.

Analyzing the Elo rating system's behavior and its impact on competitive tournaments.

This study adapts optimization techniques for better performance in Wasserstein space.

New techniques improve solutions to complex mathematical problems.

New method improves optimization in machine learning with efficient training.

A look at various types of convergence in signed measures.

Introducing a novel algorithm for nonconvex and nonsmooth optimization challenges.

Learn how data augmentation algorithms improve data analysis and model building.

This paper explores extending Euler products using the Factorization Method.

Study of phase separation through advanced numerical techniques.