3 papers
cs.DC2026
Multi-Turn Distributed Inference with Mixture of Experts for 6G Edge--Cloud Networks
Bo Liu, Haiyuan Li, Yuelin Liu +4
Mixture-of-Experts (MoE) architectures are increasingly deployed across 6G edge--cloud networks, where sparse activation reduces the computational footprint of each inference to on…
cs.LG2025
Cooperative Task Offloading through Asynchronous Deep Reinforcement Learning in Mobile Edge Computing for Future Networks
Yuelin Liu, Haiyuan Li, Xenofon Vasilakos +2
Future networks (including 6G) are poised to accelerate the realisation of Internet of Everything. However, it will result in a high demand for computing resources to support new s…
cs.NI2024
Towards Practical Operation of Deep Reinforcement Learning Agents in Real-World Network Management at Open RAN Edges
Haiyuan Li, Hari Madhukumar, Peizheng Li +6
Deep Reinforcement Learning (DRL) has emerged as a powerful solution for meeting the growing demands for connectivity, reliability, low latency and operational efficiency in advanc…