Research on Autonomous Driving Decision-making Strategies based Deep Reinforcement Learning. - Zixiang Wang; Hao Yan; Changsong Wei; Junyu Wang; Shi Bo; Minheng Xiao (IoTML, 2024)

Policy Gradient Methods for Risk-Sensitive Distributional Reinforcement Learning with Provable Convergence. - Minheng Xiao; Xian Yu; Lei Ying 001 (CoRR, 2024)

Multiple Greedy Quasi-Newton Methods for Saddle Point Problems. - Minheng Xiao; Shi Bo; Zhizhong Wu (CoRR, 2024)

Root Cause Attribution of Delivery Risks via Causal Discovery with Reinforcement Learning. - Shi Bo; Minheng Xiao (CoRR, 2024)

Electroencephalogram Emotion Recognition via AUC Maximization. - Minheng Xiao; Shi Bo (CoRR, 2024)

Adaptive Friction in Deep Learning: Enhancing Optimizers with Sigmoid and Tanh Function. - Hongye Zheng; Bingxing Wang; Minheng Xiao; Honglin Qin; Zhizhong Wu; Lianghao Tan (CoRR, 2024)

Dynamic Fraud Detection: Integrating Reinforcement Learning into Graph Neural Networks. - Yuxin Dong; Jianhua Yao 008; Jiajing Wang; Yingbin Liang; Shuhan Liao; Minheng Xiao (CoRR, 2024)

Likelihood Reward Redistribution. - Minheng Xiao; Zhenbang Jiao (CoRR, 2025)

Panda: partially approximate newton methods for distributed minimax optimization with unbalanced dimensions. - Minheng Xiao; Chengchang Liu; Cheng Chen 015; John C. S. Lui; Sen Na (Mach. Learn., 2025)