Adaptive exploration policy for exploration-exploitation tradeoff in continuous action control optimization. - Min Li 026; Tianyi Huang; William Zhu 001 (Int. J. Mach. Learn. Cybern., 2021)

A CNN-based policy for optimizing continuous action control by learning state sequences. - Tianyi Huang; Min Li 026; Xiaolong Qin; William Zhu 001 (Neurocomputing, 2022)

ACP based reinforcement learning for long-term recommender system. - Tianyi Huang; Min Li 026; William Zhu 001 (Int. J. Mach. Learn. Cybern., 2022)

Clustering experience replay for the effective exploitation in reinforcement learning. - Min Li 026; Tianyi Huang; William Zhu 001 (Pattern Recognit., 2022)

Local density based on weighted K-nearest neighbors for density peaks clustering. - Sifan Ding; Min Li 026; Tianyi Huang; William Zhu 001 (Knowl. Based Syst., 2024)

Multi-view reinforcement learning for sequential decision-making with insufficient state information. - Min Li 026; William Zhu 001; Shiping Wang (Int. J. Mach. Learn. Cybern., 2024)