82 citations · 84 across the 3 of their papers we have counts for
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cs.LG2026
Rethinking Ratio-Based Trust Regions for Policy Optimization in Multi-Agent Reinforcement Learning
Chulabhaya Wijesundara, Andrea Baisero, Zhongheng Li +3
Centralized training with decentralized execution (CTDE) is a standard framework for cooperative multi-agent policy-gradient reinforcement learning, allowing agents to learn from j…
cs.LG2019★ 82 cited
Feature Learning Viewpoint of AdaBoost and a New Algorithm
Fei Wang, Zhongheng Li, Fang He +3
The AdaBoost algorithm has the superiority of resisting overfitting. Understanding the mysteries of this phenomena is a very fascinating fundamental theoretical problem. Many studi…