Analysis of carbon emissions from transportation in Beijing. - Jiang Chen; Han Wang 016; Xin Zhang; Sihan Chen; Zongyu Bao (Int. J. Serv. Technol. Manag., 2016)

Robust Convergence Analysis of Three-Operator Splitting. - Han Wang 016; Mahyar Fazlyab; Shaoru Chen; Victor M. Preciado (Allerton, 2019)

Robust Closed-loop Model Predictive Control via System Level Synthesis. - Shaoru Chen; Han Wang 016; Manfred Morari; Victor M. Preciado; Nikolai Matni (CDC, 2020)

Large-Scale System Identification Using a Randomized SVD. - Han Wang 016; James Anderson 001 (ACC, 2022)

FedADMM: A federated primal-dual algorithm allowing partial participation. - Han Wang 016; Siddartha Marella; James Anderson 001 (CDC, 2022)

Learning Linear Models Using Distributed Iterative Hessian Sketching. - Han Wang 016; James Anderson 001 (L4DC, 2022)

Learning Personalized Models with Clustered System Identification. - Leonardo F. Toso; Han Wang 016; James Anderson 001 (CDC, 2023)

FedSysID: A Federated Approach to Sample-Efficient System Identification. - Han Wang 016; Leonardo Felipe Toso; James Anderson 001 (L4DC, 2023)

Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates. - Guangchen Lan; Han Wang 016; James Anderson 001; Christopher G. Brinton; Vaneet Aggarwal (NeurIPS, 2023)

Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity. - Han Wang 016; Aritra Mitra; Hamed Hassani; George J. Pappas; James Anderson 001 (CoRR, 2023)

Oracle Complexity Reduction for Model-Free LQR: A Stochastic Variance-Reduced Policy Gradient Approach. - Leonardo F. Toso; Han Wang 016; James Anderson 001 (ACC, 2024)

Asynchronous Heterogeneous Linear Quadratic Regulator Design. - Leonardo F. Toso; Han Wang 016; James Anderson 001 (CDC, 2024)

Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning. - Chenyu Zhang 002; Han Wang 016; Aritra Mitra; James Anderson 001 (ICLR, 2024)

Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments. - Han Wang 016; Sihong He; Zhili Zhang; Fei Miao; James Anderson 001 (ICML, 2024)

Meta-learning linear quadratic regulators: A policy gradient MAML approach for model-free LQR. - Leonardo Felipe Toso; Donglin Zhan; James Anderson 001; Han Wang 016 (L4DC, 2024)

Federated TD Learning with Linear Function Approximation under Environmental Heterogeneity. - Han Wang 016; Aritra Mitra; Hamed Hassani; George J. Pappas; James Anderson 001 (Trans. Mach. Learn. Res., 2024)