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Christoph Dann — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Christoph Dann
19
papers ·
286
citations ·
16
h-index
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Semantic Scholar ↗
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Most-cited papers
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning
2017 · 103 citations
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy
2019 · 87 citations
Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation
2022 · 26 citations
On Oracle-Efficient PAC RL with Rich Observations
2018 · 20 citations
Policy Certificates: Towards Accountable Reinforcement Learning
2018 · 19 citations
Regret Bound Balancing and Elimination for Model Selection in Bandits and RL
2020 · 12 citations
Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning
2021 · 5 citations
A Model Selection Approach for Corruption Robust Reinforcement Learning
2021 · 4 citations
A Minimaximalist Approach to Reinforcement Learning from Human Feedback
2024 · 3 citations
Memory Lens: How Much Memory Does an Agent Use?
2016 · 2 citations
Reinforcement Learning with Feedback Graphs
2020 · 2 citations
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning
2022 · 2 citations
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations
2021 · 1 citations
Theoretical Foundations and Effective Algorithms for Policy-Aware Simulator Learning
2026
Design Considerations in Offline Preference-based RL
2025
Top co-authors
Mehryar Mohri
· 6
Julian Zimmert
· 5
Alekh Agarwal
· 4
Yishay Mansour
· 4
Ayush Sekhari
· 3
Chen-Yu Wei
· 3
Emma Brunskill
· 3
Karthik Sridharan
· 3
Teodor V. Marinov
· 2
Abhradeep Thakurta
· 1
Akshay Krishnamurthy
· 1
Aldo Pacchiano
· 1
Topics
Exploration
Model-Based RL
Value-Based
Safe RL
RLHF & Alignment
Policy Gradient
Offline RL
cs.LG
stat.ML
Game AI