This desktop app for hosting and running LLMs locally is rough in a few spots, but still useful right out of the box.

INGLEWOOD, Calif. – Once upon a time – in high school, to be exact – current Rams defensive end Kobie Turner played tight end. He put that catching experience to good use last week with his first ...

🔧 Combine feature selectors with classifiers and regressors in a seamless pipeline using scikit-learn compatible meta-estimators for enhanced machine learning.

High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...

Abstract: The quality of features plays an important role in the performance of recommender systems. Recognizing this, feature selection has emerged as a crucial technique in refining recommender ...

Abstract: Feature selection (FS) is a critical step in machine learning (ML) applications, particularly in the maritime transportation domain, where large-scale data from sensors, weather conditions, ...

Introduction: Functional brain networks measured by resting-state functional magnetic resonance imaging (rs-fMRI) have become a promising tool for understanding the neural mechanisms underlying ...