Anderson, James

12 publications

TMLR 2026 Model-Free Learning with Heterogeneous Dynamical Systems: A Federated LQR Approach Han Wang, Leonardo Felipe Toso, Aritra Mitra, James Anderson

AAAI 2025 Regret Analysis of Multi-Task Representation Learning for Linear-Quadratic Adaptive Control Bruce D. Lee, Leonardo F. Toso, Thomas T. Zhang, James Anderson, Nikolai Matni

CVPRW 2024 Data-Efficient and Robust Task Selection for Meta-Learning Donglin Zhan, James Anderson

TMLR 2024 Federated TD Learning with Linear Function Approximation Under Environmental Heterogeneity Han Wang, Aritra Mitra, Hamed Hassani, George J. Pappas, James Anderson

ICLR 2024 Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning Chenyu Zhang, Han Wang, Aritra Mitra, James Anderson

L4DC 2024 Meta-Learning Linear Quadratic Regulators: A Policy Gradient MAML Approach for Model-Free LQR Leonardo Felipe Toso, Donglin Zhan, James Anderson, Han Wang

ICML 2024 Momentum for the Win: Collaborative Federated Reinforcement Learning Across Heterogeneous Environments Han Wang, Sihong He, Zhili Zhang, Fei Miao, James Anderson

ICLR 2024 Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data Thomas TCK Zhang, Leonardo Felipe Toso, James Anderson, Nikolai Matni

L4DC 2023 FedSysID: A Federated Approach to Sample-Efficient System Identification Han Wang, Leonardo Felipe Toso, James Anderson

NeurIPS 2023 Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-Based Gradient Updates Guangchen Lan, Han Wang, James Anderson, Christopher Brinton, Vaneet Aggarwal

L4DC 2022 Learning Linear Models Using Distributed Iterative Hessian Sketching Han Wang, James Anderson

NeurIPSW 2022 Meta-Adaptive Stock Movement Prediction with Two-Stage Representation Learning Donglin Zhan, Yusheng Dai, Yiwei Dong, Jinghai He, Zhenyi Wang, James Anderson