4 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.MA2024★ 3 cited
JointPPO: Diving Deeper into the Effectiveness of PPO in Multi-Agent Reinforcement Learning
Chenxing Liu, Guizhong Liu
While Centralized Training with Decentralized Execution (CTDE) has become the prevailing paradigm in Multi-Agent Reinforcement Learning (MARL), it may not be suitable for scenarios…
cs.CV2023★ 1 cited
Federated Continual Novel Class Learning
Lixu Wang, Chenxi Liu, Junfeng Guo +4
In a privacy-focused era, Federated Learning (FL) has emerged as a promising machine learning technique. However, most existing FL studies assume that the data distribution remains…
cs.LG2023★ 4 cited
DEJA VU: Continual Model Generalization For Unseen Domains
Chenxi Liu, Lixu Wang, Lingjuan Lyu +3
In real-world applications, deep learning models often run in non-stationary environments where the target data distribution continually shifts over time. There have been numerous…