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Multi-Task Imitation Learning for Linear Dynamical Systems


Dec 01, 2022
Thomas T. Zhang, Katie Kang, Bruce D. Lee, Claire Tomlin, Sergey Levine, Stephen Tu, Nikolai Matni

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Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning


Oct 05, 2022
David Brandfonbrener, Stephen Tu, Avi Singh, Stefan Welker, Chad Boodoo, Nikolai Matni, Jake Varley

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Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation


Sep 24, 2022
Xuesu Xiao, Tingnan Zhang, Krzysztof Choromanski, Edward Lee, Anthony Francis, Jake Varley, Stephen Tu, Sumeet Singh, Peng Xu, Fei Xia, Sven Mikael Persson, Dmitry Kalashnikov, Leila Takayama, Roy Frostig, Jie Tan, Carolina Parada, Vikas Sindhwani

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Learning with little mixing


Jun 16, 2022
Ingvar Ziemann, Stephen Tu

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TaSIL: Taylor Series Imitation Learning


May 30, 2022
Daniel Pfrommer, Thomas T. C. K. Zhang, Stephen Tu, Nikolai Matni

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Learning from many trajectories


Mar 31, 2022
Stephen Tu, Roy Frostig, Mahdi Soltanolkotabi

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On the Generalization of Representations in Reinforcement Learning


Mar 01, 2022
Charline Le Lan, Stephen Tu, Adam Oberman, Rishabh Agarwal, Marc G. Bellemare

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* Accepted at AISTATS22 

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Adversarially Robust Stability Certificates can be Sample-Efficient


Dec 20, 2021
Thomas T. C. K. Zhang, Stephen Tu, Nicholas M. Boffi, Jean-Jacques E. Slotine, Nikolai Matni

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Learning Robust Output Control Barrier Functions from Safe Expert Demonstrations


Nov 18, 2021
Lars Lindemann, Alexander Robey, Lejun Jiang, Stephen Tu, Nikolai Matni

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* 30 pages, submitted to the IEEE Transactions on Automatic Control 

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Random features for adaptive nonlinear control and prediction


Jun 07, 2021
Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine

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