IEEE

Friedkin-Johnsen Model is Distributed Gradient Descent

Abstract: The Friedkin-Johnsen (FJ) model describes how agents adjust their opinions through repeated interactions while accounting for the influence of agents who are partially stubborn. In this ...
IEEE

AlphaGrad: Normalized Gradient Descent for Adaptive Multi-Loss Functions in EEG-Based Motor Imagery Classification

Abstract: In this study, we propose AlphaGrad, a novel adaptive loss blending strategy for optimizing multi-task learning (MTL) models in motor imagery (MI)-based electroencephalography (EEG) ...
C&EN

Predicting the Properties of IL-Solvent Electrolytes Using a Hybrid Support Vector Classification and Gradient Boosting Regression (SVC-GBR) Framework

Henry Krumb School of Mines, Earth and Environmental Engineering Department, Columbia University, New York, New York 10027, United States ...
Frontiers

Evaluating machine learning models for stroke prediction based on clinical variables

Introduction: Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as ...