Bruce D. Lee

According to our database, Bruce D. Lee authored at least 23 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Bounded Ratio Reinforcement Learning.

Yunke Ao, Le Chen, Bruce D. Lee, Assefa S. Wahd, Aline Czarnobai, Philipp Fürnstahl, Bernhard Schölkopf, Andreas Krause

CoRR, April, 2026

Model-Based Reinforcement Learning for Control under Time-Varying Dynamics.

Klemens Iten, Bruce D. Lee, Chenhao Li, Lenart Treven, Andreas Krause, Bhavya Sukhija

CoRR, April, 2026

Optimistic Online LQR via Intrinsic Rewards.

Marcell Bartos, Bruce D. Lee, Lenart Treven, Andreas Krause, Florian Dörfler, Melanie N. Zeilinger

CoRR, March, 2026

Statistical Efficiency of Single- and Multi-step Models for Forecasting and Control.

Anne Somalwar, Bruce D. Lee, George J. Pappas, Nikolai Matni

CoRR, March, 2026

2025

Performance-Robustness Tradeoffs in Adversarially Robust Control and Estimation.

Bruce D. Lee, Thomas T. C. K. Zhang, Hamed Hassani, Nikolai Matni

IEEE Trans. Autom. Control., May, 2025

Logarithmic Regret for Nonlinear Control.

James Wang, Bruce D. Lee, Ingvar M. Ziemann, Nikolai Matni

Proceedings of the 7th Annual Learning for Dynamics & Control Conference, 2025

Domain Randomization is Sample Efficient for Linear Quadratic Control.

Tesshu Fujinami, Bruce D. Lee, Nikolai Matni, George J. Pappas

Proceedings of the 7th Annual Learning for Dynamics & Control Conference, 2025

Learning with Imperfect Models: When Multi-step Prediction Mitigates Compounding Error.

Anne Somalwar, Bruce D. Lee, George J. Pappas, Nikolai Matni

Proceedings of the 64th IEEE Conference on Decision and Control, 2025

Policy Gradient for LQR with Domain Randomization.

Tesshu Fujinami, Bruce D. Lee, Nikolai Matni, George J. Pappas

Proceedings of the 64th IEEE Conference on Decision and Control, 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

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples.

Thomas T. Zhang, Bruce D. Lee, Ingvar M. Ziemann, George J. Pappas, Nikolai Matni

CoRR, 2024

Regret Analysis of Multi-task Representation Learning for Linear-Quadratic Adaptive Control.

Bruce D. Lee, Leonardo F. Toso, Thomas T. C. K. Zhang, James Anderson, Nikolai Matni

CoRR, 2024

Nonasymptotic regret analysis of adaptive linear quadratic control with model misspecification.

Bruce D. Lee, Anders Rantzer, Nikolai Matni

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Uncertainty-Aware Deployment of Pre-trained Language-Conditioned Imitation Learning Policies.

Bo Wu, Bruce D. Lee, Kostas Daniilidis, Bernadette Bucher, Nikolai Matni

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples.

Thomas T. C. K. Zhang, Bruce D. Lee, Ingvar M. Ziemann, George J. Pappas, Nikolai Matni

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Active Learning for Control-Oriented Identification of Nonlinear Systems.

Bruce D. Lee, Ingvar M. Ziemann, George J. Pappas, Nikolai Matni

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

2023

Multi-Task Imitation Learning for Linear Dynamical Systems.

Thomas T. C. K. Zhang, Katie Kang, Bruce D. Lee, Claire J. Tomlin, Sergey Levine, Stephen Tu, Nikolai Matni

Proceedings of the Learning for Dynamics and Control Conference, 2023

A Tutorial on the Non-Asymptotic Theory of System Identification.

Ingvar M. Ziemann, Anastasios Tsiamis, Bruce D. Lee, Yassir Jedra, Nikolai Matni, George J. Pappas

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

The Fundamental Limitations of Learning Linear-Quadratic Regulators.

Bruce D. Lee, Ingvar M. Ziemann, Anastasios Tsiamis, Henrik Sandberg, Nikolai Matni

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Adversarial Tradeoffs in Robust State Estimation.

Thomas T. C. K. Zhang, Bruce D. Lee, Hamed Hassani, Nikolai Matni

Proceedings of the American Control Conference, 2023

2022

Performance-Robustness Tradeoffs in Adversarially Robust Linear-Quadratic Control.

Bruce D. Lee, Thomas T. C. K. Zhang, Hamed Hassani, Nikolai Matni

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021

Adversarial Tradeoffs in Linear Inverse Problems and Robust State Estimation.

Bruce D. Lee, Thomas T. C. K. Zhang, Hamed Hassani, Nikolai Matni

CoRR, 2021

How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?

Jingxi Xu, Bruce D. Lee, Nikolai Matni, Dinesh Jayaraman

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021