Hongyi Zhang

2025

Enabling efficient and low-effort decentralized federated learning with the EdgeFL framework

EdgeFL: A Lightweight Decentralized Federated Learning Framework

QuaFedAsync: Quality-based Asynchronous Federated Learning for the Embedded Systems

Multi-Agent Reinforcement Learning in Dynamic Industrial Context

Deep Reinforcement Learning for Multiple Agents in a Decentralized Architecture: A Case Study in the Telecommunication Domain

Deep Reinforcement Learning in a Dynamic Environment: A Case Study in the Telecommunication Industry

2022

Towards Real-World Federated Learning: Empirical Studies in the Domain of Embedded Systems

Autonomous Navigation and Configuration of Integrated Access Backhauling for UAV Base Station Using Reinforcement Learning

End-to-End Federated Learning for Autonomous Driving Vehicles

Real-time end-to-end federated learning: An automotive case study

AF-DNDF: Asynchronous Federated Learning of Deep Neural Decision Forests

Towards Continuous Data Collection from In-service Products: Exploring the Relation between Data Dimensions and Collection Challenges

Towards Federated Learning: A Case Study in the Telecommunication Domain

Engineering Federated Learning Systems: A Literature Review

Federated learning systems: Architecture alternatives