Publications

Under Review

• W. Huo, C. Liu, K. Ding, K. H. Johansson, L. Shi, “Federated Cubic Regularized Newton Learning with Sparsification-amplified Differential Privacy”.
• W. Huo, X. Chen, L. Huang, K. H. Johansson, L. Shi, “Differentially Private Dual Gradient Tracking for Distributed Resource Allocation over Directed Networks”.
• X. Chen, W. Huo, K. Ding, S. Dey, L. Shi, “Communication-efficient and Differentially-private Distributed Nash Equilibrium Seeking with Linear Convergence”.
• X. Chen, W. Huo, Y. Wu, S. Dey, L. Shi, “An Efficient Distributed Nash Equilibrium Seeking with Compressed and Event-triggered Communication”.

Journal

• W. Huo, X. Chen, K. Ding, S. Dey, L. Shi, “Compression-based Privacy Preservation for Distributed Nash Equilibrium Seeking in Aggregative Games”, IEEE Control System Letters (L-CSS).
• W. Huo, K. F. E. Tsang, Y. Yan, K. H. Johansson, L. Shi, “Distributed Nash Equilibrium Seeking with Stochastic Event-triggered Mechanism”, Automatica, 162, p.111486, 2024.
• W. Huo, L. Huang, S. Dey, L. Shi, “Neural Network-based Distributed Generalized Nash Equilibrium Seeking for Uncertain Nonlinear Multi-agent Systems”, IEEE Transactions on Control of Network Systems.
• M. Huang^*, L. Huang^*, Y. Zhong^*, H. Yang^*, X. Chen^*, W. Huo^*, J. Wang, F. Zhang, B. Bai, L. Shi, “MILP Acceleration: A Survey from Perspectives of Simplex Initialization and Learning-Based Branch and Bound”, Journal of the Operations Research Society of China, 1-55, 2023.
• X. Tang, W. Huo, Y. Yuan, X. Li, L. Shi, H. Ding, J. Kurths, “Dynamical Network Size Estimation from Local Observations”, New Journal of Physics, vol. 22, no. 9, pp. 093031, 2020.

Conference

• L. Huang^*, X. Chen^*, W. Huo^*, J. Wang, F. Zhang, B. Bai, L. Shi, “Improving Primal Heuristics for Mixed Integer Programming Problems based on Problem Reduction: A Learning-based Approach”, in the 2022 17th International Conference on Control, Automation, Robotics and Vision (ICARCV), pp. 181-186.

[* denotes equal contribution]