Risk-averse Learning with Non-Stationary Distributions
S. Wang, Z. Wang, X. Yi, M. M. Zavlanos, K. H. Johansson, S. Hirche
Submitted
Policy Evaluation in Distributional LQR (Extended Version)
Z. Wang, Y. Gao, S. Wang, M. M. Zavlanos, A. Abate, and K. H. Johansson
Constrained Optimization with Decision-Dependent Distributions
Z. Wang, C. Liu, T. Parisini, M. M. Zavlanos, and K. H. Johansson
Asymmetric Feedback Learning in Online Convex Games
Z. Wang, X. Yi, Y. Shen, M. M. Zavlanos, and K. H. Johansson
Outlier-Robust Distributionally Robust Optimization via Unbalanced Optimal Transport
Z. Wang, Y. Shen, M. M. Zavlanos, and K. H. Johansson
NeurIPS-24. Annual Conference on Neural Information Processing Systems, 2024.
Policy Evaluation in Distributional LQR
L4DC-23. Learning for Dynamics and Control, 2023. (Oral Presentation)
Risk-Averse No-Regret Learning in Online Convex Games
Z. Wang, Y. Shen, and M. M. Zavlanos
ICML-22. International Conference on Machine Learning, 2022.
Distributed Dynamic Event-Triggered Communication and Control for Multi-Agent Consensus: A Hybrid System Approach
Z. Wang, Y. Gao, Y. Liu, S. Wang, and L. Wu
Information Science. 618: 191-208. 2022.
Online Learning of Nash Equilibria in Risk-Averse Games
ACC-24. American Control Conference, 2024.
Convergence Analysis of the Best Response Algorithm for Time-Varying Games
CDC-23. IEEE Conference on Decision and Control, 2023.
A Zeroth-Order Momentum Method for Risk-Averse Online Convex Games
Z. Wang, Y. Shen, Z. I. Bell, S. Nivison, M. M. Zavlanos, and K. H. Johansson
CDC-22. IEEE Conference on Decision and Control, 2022.