1 citations · 4 across the 13 of their papers we have counts for
5 papers · 1 filter
Learn How to Query from Unlabeled Data Streams in Federated Learning
Yuchang Sun, Xinran Li, Tao Lin +1
Federated learning (FL) enables collaborative learning among decentralized clients while safeguarding the privacy of their local data. Existing studies on FL typically assume offli…
Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning
Xinran Li, Ling Pan, Jun Zhang
In multi-agent reinforcement learning (MARL), parameter sharing is commonly employed to enhance sample efficiency. However, the popular approach of full parameter sharing often lea…
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…
Reinforcement Learning with Intrinsically Motivated Feedback Graph for Lost-sales Inventory Control
Zifan Liu, Xinran Li, Shibo Chen +3
Reinforcement learning (RL) has proven to be well-performed and general-purpose in the inventory control (IC). However, further improvement of RL algorithms in the IC domain is imp…
Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning
Xinran Li, Zifan Liu, Shibo Chen +1
In multi-agent reinforcement learning (MARL), effective exploration is critical, especially in sparse reward environments. Although introducing global intrinsic rewards can foster…