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Daniel Russo — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Daniel Russo
9
papers ·
162
citations ·
19
h-index
Google Scholar ↗
Semantic Scholar ↗
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Most-cited papers
Deep Exploration via Randomized Value Functions
2017 · 68 citations
A Tutorial on Thompson Sampling
2017 · 39 citations
A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation
2018 · 31 citations
Worst-Case Regret Bounds for Exploration via Randomized Value Functions
2019 · 16 citations
On Linear Convergence of Policy Gradient Methods for Finite MDPs
2020 · 3 citations
Optimizing Audio Recommendations for the Long-Term: A Reinforcement Learning Perspective
2023 · 2 citations
Approximation Benefits of Policy Gradient Methods with Aggregated States
2020 · 1 citations
On the Limited Representational Power of Value Functions and its Links to Statistical (In)Efficiency
2024
Top co-authors
Benjamin Van Roy
· 2
Ian Osband
· 2
Jalaj Bhandari
· 2
Abbas Kazerouni
· 1
and Zheng Wen
· 1
David Cheikhi
· 1
Lucas Maystre
· 1
Raghav Singal
· 1
Yu Zhao
· 1
Zheng Wen
· 1
Topics
Value-Based
Model-Based RL
Exploration
Policy Gradient
Offline RL