Landslides pose a significant threat to people and the environment worldwide. Researchers from the Leibniz Center for ...

In contrast to prior studies that relied on deep learning models with low transparency, or balanced datasets that fail to ...

Researchers investigate reinforcement learning for climate adaptation, demonstrating its effectiveness in optimizing coastal ...

Al-Zahrani, F. (2025) Securing Consumer Banking Websites Using Machine Learning: A Mathematical and Practical Approach (Working 2024). Journal of Computer and Communications, 13, 21-29. doi: ...

As institutions evaluate AI-powered LMS platforms, they should prioritize transparency, security, data control, and ...

Researchers from UNC Chapel Hill have proposed SYMBOLIC-MOE, a symbolic, text-based, and gradient-free Mixture-of-Experts framework to enable adaptive instance-level mixing of pre-trained LLM experts.

To address these challenges, we propose an Adaptive Federated Meta Learning Framework with Multi-Objectives and Context-Awareness (AdaFML). This framework aims to achieve multiple objectives, ...

Our goal is to provide a federated learning framework that is both secure, scalable and easy-to-use. We believe that that minimal code change should be needed to progress from early proof-of-concepts ...

Under the control framework, adaptive ELM-based control strategies are proposed to suppress the influence of the uncertainties and disturbances layer-by-layer, combining with the minimum learning ...

This project will develop and apply a domain-specific scientific machine learning (SciML) framework in which a physics-informed machine learning will assimilate infrared satellite data to provide ...