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cs.LG2024
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…
cs.LG2024★ 3 cited
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…