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Emma Brunskill โ most-cited papers & profile ยท Reinforcement Learning
โ authors
ยท
overview
Emma Brunskill
44
papers ยท
641
citations ยท
43
h-index
Laboratoire d'Informatique de Paris-Nord ยท Carnegie Mellon University ยท Stanford University
Google Scholar โ
Semantic Scholar โ
OpenAlex โ
Most-cited papers
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning
2017 ยท 103 citations
Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning
2016 ยท 74 citations
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds
2019 ยท 66 citations
Off-Policy Policy Gradient with State Distribution Correction
2019 ยท 46 citations
Policy Gradient Methods for Reinforcement Learning with Function Approximation and Action-Dependent Baselines
2017 ยท 45 citations
Learning Near Optimal Policies with Low Inherent Bellman Error
2020 ยท 38 citations
Provably Good Batch Reinforcement Learning Without Great Exploration
2020 ยท 36 citations
Using Options and Covariance Testing for Long Horizon Off-Policy Policy Evaluation
2017 ยท 25 citations
Policy Certificates: Towards Accountable Reinforcement Learning
2018 ยท 19 citations
Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding
2020 ยท 18 citations
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration
2019 ยท 17 citations
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning
2021 ยท 14 citations
Combining Parametric and Nonparametric Models for Off-Policy Evaluation
2019 ยท 12 citations
Learning When-to-Treat Policies
2019 ยท 12 citations
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions
2020 ยท 12 citations
Top co-authors
Allen Nie
ยท 5
Andrea Zanette
ยท 5
Omer Gottesman
ยท 4
Philip S. Thomas
ยท 4
Ramtin Keramati
ยท 4
Yannis Flet-Berliac
ยท 4
Yao Liu
ยท 4
Zhaohan Daniel Guo
ยท 4
Finale Doshi-Velez
ยท 3
Adith Swaminathan
ยท 2
Aldo Pacchiano
ยท 2
Alekh Agarwal
ยท 2
Topics
Value-Based
Offline RL
Exploration
Model-Based RL
Safe RL
Policy Gradient
Meta-RL
RLHF & Alignment
Game AI