I am a Ph.D. student at Auburn University, working with Dr. Bo Liu in the Computational Automated Learning Laboratory (CALL). Before joining CALL, I was a Master student in the EMR & Intelligent Expert System Engineering Research Center at Zhejiang University in China.
My research interests include artificial intelligence, reinforcement learning, symbolic planning and healthcare informatics.
SDRL: Interpretable and Data-efficient Deep Reinforcement Learning Leveraging Symbolic Planning
Daoming Lyu, Fangkai Yang, Bo Liu, Steven Gustafson 33rd AAAI Conference on Artificial Intelligence (AAAI), Honolulu, USA, 2019.
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization
Bo Liu*, Tengyang Xie* (* equal contribution), Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon 32nd Conference on Neural Information Processing Systems (NIPS), Montreal, CA, 2018.
Stable and Efficient Policy Evaluation
Daoming Lyu, Bo Liu, Matthieu Geist, Wen Dong, Saad Biaz, Qi Wang IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2018.
Program Search for Machine Learning Pipelines: Leveraging Symbolic Planning and Reinforcement Learning
Fangkai Yang, Steven Gustafson, Alexander Elkholy, Daoming Lyu and Bo Liu. Genetic Programming Theory & Practice XVI, Ann Arbor, MI, 2018.
PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Making
Fangkai Yang, Daoming Lyu, Bo Liu, Steven Gustafson 27th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, 2018.
O²TD: (Near)-Optimal Off-Policy TD Learning
Bo Liu, Daoming Lyu, Wen Dong, Saad Biaz ArXiv:1704.05147
Design and Implementation of Clinical Data Integration and Management System Based on Hadoop Platform
Dao-Ming Lyu, Yu Tian, Yu Wang, Dan-Yang Tong, Wei-Wei Yin, Jing-Song Li 7th International Conference on Information Technology in Medicine and Education (ITME), 2015