Latest Articles for Machine Learning

Research highlights strategies to enhance SAM for medical imaging tasks.

Introducing FedFisher, an innovative algorithm for efficient federated learning.

A new tool offers flexible definitions of fairness for machine learning analysis.

A new method improves how robots track objects in complex environments.

Discover the Stochastic Moving Ball Approximation method for solving complex optimization problems.

New method improves image classification with minimal data using unlabeled images.

Researchers develop new ways to analyze web data from Common Crawl archives.

A look at how compact methods improve data fitting for large datasets.

Self-supervised learning improves model performance with less labeled data.

Introducing a new method to enhance image segmentation for medical imaging.

Research shows how LLMs can clean data sets for summarization tasks.

Research highlights the importance of fairness in machine learning language representations.

CoNFiLD model offers efficient turbulence simulation for fluid dynamics applications.

A new training method enhances language model performance and user experience.

Exploring how neural networks can approximate functionals in data analysis.

A fresh method for creating action models from complete data.

A new method enhances the reliability of neural network predictions in regression tasks.

New techniques enhance the speed of developing compositionally complex alloys.

A new method fixes issues in machine learning models without losing accuracy.

Improving software security by detecting vulnerabilities before exploitation.

Transfer learning uses knowledge from one area to improve tasks in another.

A new method improves efficiency in handling requests for large language models.

A new approach enhances predictions in tabular data using LLMs.

Exploring methods to achieve fairness in classification systems without sacrificing performance.

A new method enhances image clustering despite unknown category counts.

A new method improves understanding of socioeconomic models using satellite imagery.

Researching techniques to reduce noise in quantum computing using neural networks.

Combining OOD detection and Conformal Prediction enhances model reliability.

New method reveals vulnerabilities in no-reference image and video quality assessments.

A new approach using RGCNs improves sentiment classification from text data.

A new method improves link prediction by addressing noisy and incomplete data.

Introducing TrainlessGNN for faster node labeling in TAGs without traditional training methods.

This paper reviews the benefits of many-shot learning in language models.

A study highlights CLIP's reliance on spurious features in image recognition.

A new method enhances memory replay for graph learning while ensuring privacy.

This article highlights new methods for calculating derivatives in nonsmooth functions relevant to machine learning.

A novel method using binary vectors to represent language concepts efficiently.

New methods enhance communication efficiency using multiple sensors.

This study enhances emotion recognition through multi-modal self-supervised methods.

An overview of prompting and prefix-tuning in transformer models.