25 citations · 55 across the 17 of their papers we have counts for
24 papers
Demystify Self-Attention in Vision Transformers from a Semantic Perspective: Analysis and Application
Leijie Wu, Song Guo, Yaohong Ding +4
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,…
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning
Wei Huang, Chunrui Liu, Yilan Chen +2
PAC-Bayesian is an analysis framework where the training error can be expressed as the weighted average of the hypotheses in the posterior distribution whilst incorporating the pri…
Regularize! Don't Mix: Multi-Agent Reinforcement Learning without Explicit Centralized Structures
Chapman Siu, Jason Traish, Richard Yi Da Xu
We propose using regularization for Multi-Agent Reinforcement Learning rather than learning explicit cooperative structures called {\em Multi-Agent Regularized Q-learning} (MARQ).…
Dual Behavior Regularized Reinforcement Learning
Chapman Siu, Jason Traish, Richard Yi Da Xu
Reinforcement learning has been shown to perform a range of complex tasks through interaction with an environment or collected leveraging experience. However, many of these approac…
Greedy UnMixing for Q-Learning in Multi-Agent Reinforcement Learning
Chapman Siu, Jason Traish, Richard Yi Da Xu
This paper introduces Greedy UnMix (GUM) for cooperative multi-agent reinforcement learning (MARL). Greedy UnMix aims to avoid scenarios where MARL methods fail due to overestimati…
Alleviating Mode Collapse in GAN via Diversity Penalty Module
Sen Pei, Richard Yi Da Xu, Shiming Xiang +1
The vanilla GAN (Goodfellow et al. 2014) suffers from mode collapse deeply, which usually manifests as that the images generated by generators tend to have a high similarity amongs…