Mingsheng Fu is currently a research fellow in the Future Resilient Systems since Jul 2021. He was a research fellow in Nanyang Technological University. He received his Ph.D. degree in computer science from the University of Electronic Science and Technology of China, Chengdu, in 2019. His current research interests are Neural Networks, Reinforcement Learning, and Recommender Systems.
- 2019 Ph.D. in Computer Science, University of Electronic Science and Technology of China, China
- 2012 BS. in Information Management and Information System, University of Electronic Science and Technology of China, China
- Fu M, Agrawal A, Irissappane A A, et al. Deep Reinforcement Learning Framework for Category-Based Item Recommendation[J]. IEEE Transactions on Cybernetics, 2021.
- Yang Z, Qu H, Fu M, et al. A Maximum Divergence Approach to Optimal Policy in Deep Reinforcement Learning[J]. IEEE Transactions on Cybernetics, 2021.
- Huang L, Fu M, Li F, et al. A deep reinforcement learning based long-term recommender system[J]. Knowledge-Based Systems, 2021, 213: 106706.
- Huang L, Fu M, Qu H, et al. A deep reinforcement learning-based method applied for solving multi-agent defense and attack problems[J]. Expert Systems with Applications, 2021, 176: 114896.
- Fu M, Qu H, Yi Z, et al. A novel deep learning-based collaborative filtering model for recommendation system[J]. IEEE transactions on cybernetics, 2018, 49(3): 1084-1096.
- Fu M, Qu H, Moges D, et al. Attention based collaborative filtering[J]. Neurocomputing, 2018, 311: 88-98.
- Fu M, Qu H, Huang L, et al. Bag of meta-words: A novel method to represent document for the sentiment classification[J]. Expert Systems with Applications, 2018, 113: 33-43.
- Xi R, Hou M, Fu M, et al. Deep dilated convolution on multimodality time series for human activity recognition[C]//2018 International Joint Conference on Neural Networks (IJCNN). IEEE, 2018: 1-8.
- Xi R, Li M, Hou M, et al. Deep dilation on multimodality time series for human activity recognition[J]. IEEE Access, 2018, 6: 53381-53396.