Research

Working Papers

Wang, Q.H., Xu, S.H, Ho, C. P., Petrik, M., Policy Gradient for Robust Markov Decision Processes, JMLR major revision.
Wang, Q.H., Ruan, H.L., Zhou, S.Y., Chen, Z., Ho, C. P., Risk-Aware Robust Satisficing Markov Decision Processes, under revision.
Ruan, H.L., Wang, Q.H., Chen, Z., Ho, C. P., Distributionally Reward-Robust Risk-Sensitive MDPs, under revision.
Zha, Y.Q., Wang, Q.H., Ho, C. P., Petrik, M., On the Convergence of Risk-Averse MDPs under Uncertainty with Two-Timescale Rule.
Wang, Q.H., Ho, C. P., Fast Policy Iteration for Singularly Perturbed MDPs.

Wang, Q.H., Zha, Y.Q., Ho, C. P., Petrik, M., Provable Policy Gradient for Robust Average-Reward MDPs Beyond Rectangularity, accepted in the 42th International Conference on Machine Learning (ICML), 2025.
Wang, Q.H., Ho, C. P., Petrik, M., Policy Gradient in Robust MDPs with Global Convergence Guarantee, accepted in the 40th International Conference on Machine Learning (ICML), 2023.

MSc students at City University of Hong Kong (co-supervised with Dr. Chin Pang Ho):

Qu Tong, Li Jiaxin and Zhang Junjie, “Recommendation System for Creating Courses”, 2021.
Wong Ka Wai, Li Ka Ho, and Choi Sheung Shing, “Recommendation System for Creating Courses”, 2021.

Journal: Journal of Machine Learning Research, Operations Research Letters, Machine Learning, Journal of Artificial Intelligence Research, Expert Systems with Applications
Conference: AISTATS 2023/2026, NeurIPS 2023/2025, ICLR 2024, ICML 2024, AAAI 2026