3 papers
cs.RO2024
Uncertainty-Aware Deployment of Pre-trained Language-Conditioned Imitation Learning Policies
Bo Wu, Bruce D. Lee, Kostas Daniilidis +2
Large-scale robotic policies trained on data from diverse tasks and robotic platforms hold great promise for enabling general-purpose robots; however, reliable generalization to ne…
cs.LG2024
Regret Analysis of Multi-task Representation Learning for Linear-Quadratic Adaptive Control
Bruce D. Lee, Leonardo F. Toso, Thomas T. Zhang +2
Representation learning is a powerful tool that enables learning over large multitudes of agents or domains by enforcing that all agents operate on a shared set of learned features…
eess.SY2024
Nonasymptotic Regret Analysis of Adaptive Linear Quadratic Control with Model Misspecification
Bruce D. Lee, Anders Rantzer, Nikolai Matni
The strategy of pre-training a large model on a diverse dataset, then fine-tuning for a particular application has yielded impressive results in computer vision, natural language p…