Latest Articles for Convergence

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.

Examining how network clustering influences efficiency in decentralized systems.

Explore techniques for minimizing functions using gradient methods and their applications.

A look into how random curves model physical systems and phase transitions.

Recent developments enhance the Arimoto-Blahut algorithm for channel capacity calculations.

Exploring the behavior of dynamical systems with neutral fixed points and empirical measures.

New approaches to tackle complex linear systems efficiently.

Research on neural networks reveals behaviors of heavy-tailed distributions.

A look into fluid mechanics, covering key concepts and applications.

A new method enhances architecture search for deep learning models.

A look at random variables and Markov chains across various fields.

A new method improves neural network training using a hybrid optimization approach.

A new method employs symmetries in neural networks to improve quantum system predictions.

A new method improves parameter selection for complex-valued neural networks in digital communication.

Introducing a method that improves efficiency in solving bilevel optimization problems.

Methods for transforming complex data into clear visual formats.

A method that improves finite element analysis using arbitrary meshes.

Exploring how random matrix eigenvalues behave over time and reach stable distributions.

Improving optimization techniques for real-valued functions using a modified Mixed Newton Method.