IEEE

Asynchronous Federated Learning with non-convex client objective functions and heterogeneous dataset

Abstract: Federated Learning is a distributed machine learning paradigm that enables model training across decentralized devices holding local data, thereby preserving data privacy and reducing the ...
InfoQ

Nuxt Introduces Native Request Cancellation and Async Handler Extraction for Performance Gains

Nuxt 4.2 elevates the developer experience with native abort control for data fetching, improved error handling, and ...
IEEE

O-RAN-Based Digital Twin Function Virtualization for Sustainable IoV Service Response: An Asynchronous Hierarchical Reinforcement Learning Approach

Abstract: Digital Twin for Vehicular Networks (DTVN) continuously simulates and optimizes vehicle behaviors to support emerging 6G Internet-of-Vehicle (IoV) applications such as DT-assisted autonomous ...