2 citations · 2 across the 1 of their papers we have counts for
3 papers
cs.LG2025
Diffusion Classifier-Driven Reward for Offline Preference-based Reinforcement Learning
Teng Pang, Bingzheng Wang, Guoqiang Wu +1
Offline preference-based reinforcement learning (PbRL) mitigates the need for reward definition, aligning with human preferences via preference-driven reward feedback without inter…
cs.LG2024★ 2 cited
Towards Macro-AUC oriented Imbalanced Multi-Label Continual Learning
Yan Zhang, Guoqiang Wu, Bingzheng Wang +3
In Continual Learning (CL), while existing work primarily focuses on the multi-class classification task, there has been limited research on Multi-Label Learning (MLL). In practice…
cs.LG2023
DiffAIL: Diffusion Adversarial Imitation Learning
Bingzheng Wang, Guoqiang Wu, Teng Pang +2
Imitation learning aims to solve the problem of defining reward functions in real-world decision-making tasks. The current popular approach is the Adversarial Imitation Learning (A…