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20162022
most citedNon-Asymptotic Analysis of Robust Control from Coarse-Grained Identification

54 citations · 217 across the 12 of their papers we have counts for

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7 papers · 1 filter

math.OC20202 cited

Safely Learning Dynamical Systems from Short Trajectories

Amir Ali Ahmadi, Abraar Chaudhry, Vikas Sindhwani +1

A fundamental challenge in learning to control an unknown dynamical system is to reduce model uncertainty by making measurements while maintaining safety. In this work, we formulat…

math.OC2019

A Tutorial on Concentration Bounds for System Identification

Nikolai Matni, Stephen Tu

We provide a brief tutorial on the use of concentration inequalities as they apply to system identification of state-space parameters of linear time invariant systems, with a focus…

math.OC2019

From self-tuning regulators to reinforcement learning and back again

Nikolai Matni, Alexandre Proutiere, Anders Rantzer +1

Machine and reinforcement learning (RL) are increasingly being applied to plan and control the behavior of autonomous systems interacting with the physical world. Examples include…

math.OC201942 cited

Certainty Equivalence is Efficient for Linear Quadratic Control

Horia Mania, Stephen Tu, Benjamin Recht

We study the performance of the certainty equivalent controller on Linear Quadratic (LQ) control problems with unknown transition dynamics. We show that for both the fully and part…

math.OC2018

Minimax Lower Bounds for -Norm Estimation

Stephen Tu, Ross Boczar, Benjamin Recht

The problem of estimating the -norm of an LTI system from noisy input/output measurements has attracted recent attention as an alternative to parameter identifi…

math.OC2018

Safely Learning to Control the Constrained Linear Quadratic Regulator

Sarah Dean, Stephen Tu, Nikolai Matni +1

We study the constrained linear quadratic regulator with unknown dynamics, addressing the tension between safety and exploration in data-driven control techniques. We present a fra…