Richard Yi Da Xu

Regularize! Don't Mix: Multi-Agent Reinforcement Learning without\n Explicit Centralized Structures

2021 · arXiv (Cornell University)

We propose using regularization for Multi-Agent Reinforcement Learning rather\nthan learning explicit cooperative structures called {\\em Multi-Agent\nRegularized Q-learning} (MARQ). Many MARL approaches leverage centralized\nstructures in order to exploit global state information or removing\ncommunication constraints when the …

Demystify Self-Attention in Vision Transformers from a Semantic Perspective: Analysis and Application

2022 · arXiv (Cornell University)

Self-attention mechanisms, especially multi-head self-attention (MSA), have achieved great success in many fields such as computer vision and natural language processing. However, many existing vision transformer (ViT) works simply inherent transformer designs from NLP to …