Papers

Preprints

• Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization [arXiv]
  S. Cen, Y. Wei, and Y. Chi, preprint. Short version at NeurIPS 2021.

Conference Proceedings

• Asynchronous Gradient Play in Zero-Sum Multi-agent Games [arXiv]
  R. Ao, S. Cen, and Y. Chi, International Conference on Learning Representations (ICLR), 2023.

• Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games [arXiv]
  S. Cen, Y. Chi, S. Du, and L. Xiao, International Conference on Learning Representations (ICLR), 2023.

• Independent Natural Policy Gradient Methods for Potential Games: Finite-time Global Convergence with Entropy Regularization [arXiv][Invited Paper]
  S. Cen, F. Chen, and Y. Chi, IEEE Conference on Decision and Control (CDC), 2022.

• Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction [arXiv] [Code]
  B. Li, S. Cen, Y. Chen, and Y. Chi, International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.

Journals

• Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence [arXiv]
  W. Zhan, S. Cen, B. Huang, Y. Chen, J. D. Lee, and Y. Chi, SIAM Journal on Optimization, accepted. Short version at OPT2021 as an oral presentation.

• Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization [arXiv][PDF] [Code]
  S. Cen, C. Cheng, Y. Chen, Y. Wei, Y. Chi, Operations Research, accepted.

  • 2021 INFORMS George Nicholson Student Paper Competition Finalist

• Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction [arXiv] [Code]
  B. Li, S. Cen, Y. Chen, and Y. Chi, Journal of Machine Learning Research, vol. 21, no. 180, pp. 1-51, 2020.

• Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data [arXiv]
  S. Cen. Zhang, Y. Chi, W. Chen and T.-Y. Liu, IEEE Trans. on Signal Processing, vol. 68, pp. 3976-3989, 2020.

• A Stochastic Semismooth Newton Method for Nonsmooth Nonconvex Optimization [arXiv]
  A. Milzarek, X. Xiao, S. Cen, Z. Wen, M. Ulbrich, SIAM Journal on Optimization.