Chen Ziyi

• Top Reviewer at The Conference on Uncertainty in Artificial Intelligence (UAI), 2023
• Founder Scholarship, 2014
• Pacemaker to Merit Student, 2014
• National Scholarship of China, Ministry of Education of China, 2013, 2011 (awarded 2 times in total)
• Honour of ``Outstanding Graduate Cadre'', 2012
• Honour of ``Excellent Student Cadre'', 2011
• The First Prize of the 8th Competition of Advanced Mathematics, 2010
• The First Prize of Physics Competition, 2009

1. S. Ma, Z. Chen, Y. Zhou, and H. Huang. Rectified robust policy optimisation for model-uncertain constrained reinforcement learning without strong duality. Transactions on Machine Learning Research (TMLR), 2025.

2. Q. He, P. Yu, Z. Chen, and H. Huang. Revisiting convergence: A study on shuffling-type gradient methods. International Conference on Machine Learning (ICML), 2025.

3. Z. Hu, T. Zheng, V. Viswanathan, Z. Chen, R. A. Rossi, Y. Wu, D. Monocha, and H. Huang. Towards optimal multi-draft speculative decoding. International Conference on Learning Representations (ICLR), 2025.

4. Z. Chen, Y. Wen, Z. Hu, and H. Huang. Robust reinforcement learning with general utility. Advances in Neural Information Processing Systems (NeurIPS), 2024.

5. Z. Chen and H. Huang. Accelerated policy gradient for s-rectangular robust MDPs with large state spaces. International Conference on Machine Learning (ICML), 2024.

6. W. Xian, Z. Chen, and H. Huang. Delving into the convergence of generalised smooth minimax optimisation. International Conference on Machine Learning (ICML), 2024.

7. Z. Chen, Y. Zhou, and H. Huang. On the hardness of constrained cooperative multi-agent reinforcement learning. International Conference on Learning Representations (ICLR), 2024.

8. J. Liu, L. He, Z. Chen, Z. Chen, Y. Hao, and D. Jiang. Context-aware EEG-based perceived stress recognition based on emotion transition paradigm. International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), IEEE, 2023, pp. 1–8.

9. Z. Chen, Y. Zhou, Y. Liang, and Z. Lu. Generalised-smooth nonconvex optimisation is as efficient as smooth nonconvex optimisation. International Conference on Machine Learning (ICML), 2023.

10. Z. Chen, Z. Hu, Q. Li, Z. Wang, and Y. Zhou. A cubic regularisation approach for finding local minimax points in nonconvex minimax optimisation. Transactions on Machine Learning Research (TMLR), 2023.

11. Z. Chen, B. Kailkhura, and Y. Zhou. An accelerated proximal algorithm for regularised nonconvex and nonsmooth bi-level optimization. Machine Learning, vol. 112, pp. 1433–1463, 2023.

12. S. Ma, Z. Chen, S. Zou, and Y. Zhou. Decentralised robust v-learning for solving Markov games with model uncertainty. Journal of Machine Learning Research (JMLR), vol. 24, no. 371, pp. 1–40, 2023.

13. Z. Xu, Z. Chen, and X. Chen. Dynamic feature-based newsvendor. ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023.

14. Z. Chen, S. Ma, and Y. Zhou. Finding correlated equilibrium of constrained Markov game: A primal-dual approach. Advances in Neural Information Processing Systems (NeurIPS), 2022.

15. Z. Chen, Y. Zhou, R.-R. Chen, and S. Zou. Sample and communication-efficient decentralised actor-critic algorithms with finite-time analysis. International Conference on Machine Learning (ICML), 2022, pp. 3794–3834.

16. Z. Chen, S. Ma, and Y. Zhou. Sample efficient stochastic policy extragradient algorithm for zero-sum Markov game. International Conference on Learning Representations (ICLR), 2022.

17. Z. Chen, Y. Zhou, and R.-R. Chen. Multi-agent off-policy TDC with near-optimal sample and communication complexities. Transactions on Machine Learning Research (TMLR), 2022.

18. S. Ma, Z. Chen, Y. Zhou, K. Ji, and Y. Liang. Data sampling affects the complexity of online SGD over dependent data. Conference on Uncertainty in Artificial Intelligence (UAI), 2022, pp. 1296–1305.

19. Z. Chen, Y. Zhou, T. Xu, and Y. Liang. Proximal gradient descent-ascent: Variable convergence under KŁ geometry. International Conference on Learning Representations (ICLR), 2021.

20. S. Ma, Z. Chen, Y. Zhou, and S. Zou. Greedy-GQ with variance reduction: Finite-time analysis and improved complexity. International Conference on Learning Representations (ICLR), 2021.

21. C. Chen, Z. Chen, Y. Zhou, and B. Kailkhura. FedCluster: Boosting the convergence of federated learning via cluster-cycling. 2020 IEEE International Conference on Big Data (Big Data), 2020, pp. 5017–5026.

• Program Committe Console: AAAI
• Reviewer: ICML, Neurips, ICLR, UAI, TMLR, AISTATS, SIOPT, IEEE CDC, IEEE TSP, IEEE TKDE