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Stephen Tu — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Stephen Tu
13
papers ·
121
citations ·
25
h-index
Google (United States)
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Most-cited papers
Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator
2017 · 27 citations
Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator
2019 · 22 citations
The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint
2018 · 20 citations
Observational Overfitting in Reinforcement Learning
2019 · 17 citations
From self-tuning regulators to reinforcement learning and back again
2019 · 16 citations
Learning from many trajectories
2022 · 9 citations
On the Generalization of Representations in Reinforcement Learning
2022 · 5 citations
Bootstrapped Representations in Reinforcement Learning
2023 · 1 citations
Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning
2022
Top co-authors
Benjamin Recht
· 3
Charline Le Lan
· 2
Nikolai Matni
· 2
Rishabh Agarwal
· 2
Adam Oberman
· 1
Alexandre Proutière
· 1
Anders Rantzer
· 1
Anna Harutyunyan
· 1
Avi Singh
· 1
Behnam Neyshabur
· 1
Chad Boodoo
· 1
David Brandfonbrener
· 1
Topics
Model-Based RL
Value-Based
Exploration
Policy Gradient
Offline RL
Safe RL
Meta-RL
stat.ML