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09/11/2023
Revisiting Energy Based Models as Policies: Ranking Noise Contrastive Estimation and Interpolating Energy Models
A crucial design decision for any robot learning pipeline is the choice ...
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06/16/2023
Bootstrapped Representations in Reinforcement Learning
In reinforcement learning (RL), state representations are key to dealing...
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06/14/2023
Agile Catching with Whole-Body MPC and Blackbox Policy Learning
We address a benchmark task in agile robotics: catching objects thrown a...
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05/20/2023
Safely Learning Dynamical Systems
A fundamental challenge in learning an unknown dynamical system is to re...
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05/18/2023
The noise level in linear regression with dependent data
We derive upper bounds for random design linear regression with dependen...
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05/16/2023
The Power of Learned Locally Linear Models for Nonlinear Policy Optimization
A common pipeline in learning-based control is to iteratively estimate a...
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12/01/2022
Multi-Task Imitation Learning for Linear Dynamical Systems
We study representation learning for efficient imitation learning over l...
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10/05/2022
Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning
We consider how to most efficiently leverage teleoperator time to collec...
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09/22/2022
Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation
Despite decades of research, existing navigation systems still face real...
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06/16/2022
Learning with little mixing
We study square loss in a realizable time-series framework with martinga...
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05/30/2022
TaSIL: Taylor Series Imitation Learning
We propose Taylor Series Imitation Learning (TaSIL), a simple augmentati...
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03/31/2022
Learning from many trajectories
We initiate a study of supervised learning from many independent sequenc...
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03/01/2022
On the Generalization of Representations in Reinforcement Learning
In reinforcement learning, state representations are used to tractably d...
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12/20/2021
Adversarially Robust Stability Certificates can be Sample-Efficient
Motivated by bridging the simulation to reality gap in the context of sa...
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11/18/2021
Learning Robust Output Control Barrier Functions from Safe Expert Demonstrations
This paper addresses learning safe control laws from expert demonstratio...
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06/07/2021
Random features for adaptive nonlinear control and prediction
A key assumption in the theory of adaptive control for nonlinear systems...
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02/18/2021
Closing the Closed-Loop Distribution Shift in Safe Imitation Learning
Commonly used optimization-based control strategies such as model-predic...
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01/16/2021
Learning Robust Hybrid Control Barrier Functions for Uncertain Systems
The need for robust control laws is especially important in safety-criti...
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11/26/2020
Regret Bounds for Adaptive Nonlinear Control
We study the problem of adaptively controlling a known discrete-time non...
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11/24/2020
Safely Learning Dynamical Systems from Short Trajectories
A fundamental challenge in learning to control an unknown dynamical syst...
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11/08/2020
Learning Hybrid Control Barrier Functions from Data
Motivated by the lack of systematic tools to obtain safe control laws fo...
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08/13/2020
Learning Stability Certificates from Data
Many existing tools in nonlinear control theory for establishing stabili...
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04/07/2020
Learning Control Barrier Functions from Expert Demonstrations
Inspired by the success of imitation and inverse reinforcement learning ...
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06/27/2019
A Tutorial on Concentration Bounds for System Identification
We provide a brief tutorial on the use of concentration inequalities as ...
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06/27/2019
From self-tuning regulators to reinforcement learning and back again
Machine and reinforcement learning (RL) are being applied to plan and co...
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05/30/2019
Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator
We study the sample complexity of approximate policy iteration (PI) for ...
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02/21/2019
Certainty Equivalent Control of LQR is Efficient
We study the performance of the certainty equivalent controller on the L...
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12/09/2018
The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint
The effectiveness of model-based versus model-free methods is a long-sta...
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09/28/2018
Minimax Lower Bounds for H_∞-Norm Estimation
The problem of estimating the H_∞-norm of an LTI system from noisy input...
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09/26/2018
Safely Learning to Control the Constrained Linear Quadratic Regulator
We study the constrained linear quadratic regulator with unknown dynamic...
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05/23/2018
Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator
We consider adaptive control of the Linear Quadratic Regulator (LQR), wh...
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04/13/2018
Learning Contracting Vector Fields For Stable Imitation Learning
We propose a new non-parametric framework for learning incrementally sta...
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02/22/2018
Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification
We prove that the ordinary least-squares (OLS) estimator attains nearly ...
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12/22/2017
Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator
Reinforcement learning (RL) has been successfully used to solve many con...
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10/04/2017
On the Sample Complexity of the Linear Quadratic Regulator
This paper addresses the optimal control problem known as the Linear Qua...
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05/31/2016
CYCLADES: Conflict-free Asynchronous Machine Learning
We present CYCLADES, a general framework for parallelizing stochastic op...
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02/17/2016
