3 citations · 3 across the 4 of their papers we have counts for
4 papers
A Federated Online Restless Bandit Framework for Cooperative Resource Allocation
Jingwen Tong, Xinran Li, Liqun Fu +2
Restless multi-armed bandits (RMABs) have been widely utilized to address resource allocation problems with Markov reward processes (MRPs). Existing works often assume that the dyn…
Two-Stage Resource Allocation in Reconfigurable Intelligent Surface Assisted Hybrid Networks via Multi-Player Bandits
Jingwen Tong, Hongliang Zhang, Liqun Fu +2
This paper considers a resource allocation problem where several Internet-of-Things (IoT) devices send data to a base station (BS) with or without the help of the reconfigurable in…
Data-Driven Online Resource Allocation for User Experience Improvement in Mobile Edge Clouds
Liqun Fu, Jingwen Tong, Tongtong Lin +1
As the cloud is pushed to the edge of the network, resource allocation for user experience improvement in mobile edge clouds (MEC) is increasingly important and faces multiple chal…
From Learning to Analytics: Improving Model Efficacy with Goal-Directed Client Selection
Jingwen Tong, Zhenzhen Chen, Liqun Fu +2
Federated learning (FL) is an appealing paradigm for learning a global model among distributed clients while preserving data privacy. Driven by the demand for high-quality user exp…