Latest Articles for Parameters

This study examines how brain activity patterns influence everyday actions.

Examining the effectiveness of self-adjusting algorithms for optimization problems.

A new method to speed up language models in natural language processing.

A new calibration method enhances precision in 4D STEM imaging.

Research reveals potential pathways for understanding new physics through cLFV.

Learn how threshold OU processes aid in predicting behavior in various fields.

A new method improves SVM training speed and accuracy with large datasets.

SGD-PH combines first-order and second-order methods for better model training performance.

Exploring how NCDEs reshape data learning and prediction.

Learn how random sketching improves our approach to inverse problems in data analysis.

This study evaluates how model size and quantization impact language model performance.

A look into the theory and applications of designs in polar spaces.

A new protocol enhances privacy and efficiency in decentralized learning.

Dynamically Composable Multi-Head Attention enhances Transformer efficiency and flexibility.

New techniques enhance the verification of deep neural networks for safer applications.

A study on multiplier polynomials and their impact on dynamical systems.

Exploring the interplay between loop quantum cosmology and inflationary models in the universe's evolution.

This article examines the optimal way to attach elastic plates to minimize energy.

A new method for predicting complex outcomes using matrix data.

Discover how cycloids help model synchronization in processes across various fields.

FlexKalmanNet improves spacecraft navigation by learning from data.

Introducing SwiLoRA, a method that optimizes training for large language models with fewer resources.

A guide to parameter identifiability and estimation in real-world modeling.

HesScale improves efficiency in machine learning by estimating the Hessian diagonal.

Research shows how math can improve predictions for multiple myeloma treatment outcomes.

New findings enhance the effectiveness of QAOA for optimization problems.

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

A look into set-valued inclusion problems in optimization and real-life applications.

Exploring how gravitational waves reveal secrets of black holes and their interactions.

Exploring the complex world of quantum difference equations and their mathematical significance.

A new benchmarking suite improves compiler autotuning efficiency and effectiveness.

MIGU enhances continuous learning in language models without needing old data.

A new method estimates parameters of neuron activity using real data.

Two innovative calibration methods enhance cardiovascular model accuracy for patient care.

Grass method improves memory usage for training large language models.

A closer look at how MoE models operate and their potential benefits.

Explore how slight changes impact planetary orbits and behaviors in three-body systems.

A look at Green's functions, their derivatives, and their role in solving differential equations.

A new convolutional layer design reduces parameters and improves interpretability in AI models.

A novel method to fine-tune language models efficiently with fewer parameters.