Tran The Hung

Lecturer, Department Of Computer Science

Ph.D. (Computer Science, Paris Cité university, France, 2013)
M.S. (La Rochelle university, France, 2009)
B.S. (Hanoi University of Science and Technology, 2006)

Email: hungtt@soict.hust.edu.vn

• Artificial Intelligence
• Algorithm and Optimization
• Decision Making Systems

• Reinforcement learning (online, offline, large scale, robustness)
• Bayesian optimization
• Transfer learning

TRAN The Hung is currently a lecturer at the School of Information and Communications Technology, Hanoi University of Science and Technology (HUST). He obtained the Ph.D degree in computer science in 2013 from the Paris Cité university, France. His current research focuses on building the theoretical foundations and algorithmic principles for optimization and decision-making problems such as bandits, reinforcement learning. He is an invited reviewer and joins the program committees of leading conferences in artificial intelligence including ICML, NeurIPS, ICLR, AISTATS, AAAI.

• Hung Tran-The, Sunil Gupta, Santu Rana, Long Tran-Thanh, Svetha Venkatesh. Expected Improvement for Contextual Bandits. In Advances in Neural Information Processing Systems: Annual Conference on Neural Information Processing Systems (NeurIPS), 2022.
• Linh Le, Hung Tran-The, Sunil Gupta. Policy Learning for Off-Dynamics Reinforcement Learning with Deficient Support. To appear at AAMAS 2024.
• Hien Dang, Tho Tran, Stanley Osher, Hung Tran-The, Nhat Ho, Tan Nguyen. Neural Collapse in Deep Linear Network: From Balanced to Imbalanced Data. The 40th International Conference on Machine Learning conference (ICML), 2023.
• Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh. Improved Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. Published at the 25th International Conference on Artificial Intelligence and Statistics (AISTAT), 2022
• Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh. On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces. Transactions on Machine Learning Research Journal (TMLR), 2022.
• Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh. Bayesian Optimistic Optimization with Exponentially Decay Regret. The 38th International Conference on Machine Learning conference (ICML), 2021.
• Hung Tran-The, Sunil Gupta, Santu Rana, Ha Huong, Svetha Venkatesh. Sublinear Regret Bayesian Optimization for Unknown Search Space. In Advances in Neural Information Processing Systems: Annual Conference on Neural Information Processing Systems (NeurIPS), 2020.
• Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh. Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. Thirty-Forth AAAI conference on Artificial Intelligence (AAAI), 2020.
• Hung Tran-The and Koji Zettsu. Discovering Co-occurrence Paterns of Heterogeneous Events from Unevenly-distributed Spatiotemporal Data. In Proceedings of the IEEE International Conference on Big Data, 2017.