The ability of computers to learn on their own by using data is known as machine learning. It is closely related to ...

de Filippis, R. and Al Foysal, A. (2026) Cross-Population Transfer Learning for Antidepressant Treatment Response Prediction: A SHAP-Based Explainability Approach Using Synthetic Multi-Ethnic Data.

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

Request To Download Free Sample of This Strategic Report @- The global reinforcement learning market is experiencing a period of rapid growth, with revenue estimated to increase from approximately $3 ...

Machine learning technique teaches power-generating kites to extract energy from turbulent airflows more effectively, ...

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...

AWS, Cisco, CoreWeave, Nutanix and more make the inference case as hyperscalers, neoclouds, open clouds, and storage go ...

Crucially, detection and response must be unified across identity and data layers. An alert about unusual data access is meaningless if it is not correlated with identity risk signals. Autonomous ...

Fluid–structure interaction (FSI) governs how flowing water and air interact with marine structures—from wind turbines to underwater cables—and is critical for safe renewable energy development.

Abstract: The exponential growth in Internet-connected devices has escalated the demand for optimized network topologies to ensure high performance. Traditional optimization methods often fall short ...

Abstract: Unmanned Aerial Vehicle (UAV)-powered 5G/6G networks integrated with rechargeable wireless sensor networks (RWSNs) offer promising solutions for extending system lifetime, collecting data, ...