Hongyi Zhang
Visar 17 publikationer
Enabling efficient and low-effort decentralized federated learning with the EdgeFL framework
EdgeFL: A Lightweight Decentralized Federated Learning Framework
Advancing Edge Intelligence: Federated and Reinforcement Learning for Smarter Embedded Systems
QuaFedAsync: Quality-based Asynchronous Federated Learning for the Embedded Systems
Multi-Agent Reinforcement Learning in Dynamic Industrial Context
Deep Reinforcement Learning in a Dynamic Environment: A Case Study in the Telecommunication Industry
Towards Real-World Federated Learning: Empirical Studies in the Domain of Embedded Systems
Real-time end-to-end federated learning: An automotive case study
End-to-End Federated Learning for Autonomous Driving Vehicles
AF-DNDF: Asynchronous Federated Learning of Deep Neural Decision Forests
Towards Federated Learning: A Case Study in the Telecommunication Domain
Engineering Federated Learning Systems: A Literature Review
Federated learning systems: Architecture alternatives
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Visar 1 forskningsprojekt
Software Engineering for AI/ML/DL