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Yuejie Chi — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Yuejie Chi
51
papers ·
295
citations ·
34
h-index
Yale University · Carnegie Mellon University
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Semantic Scholar ↗
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Most-cited papers
Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization
2020 · 41 citations
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
2020 · 29 citations
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
2021 · 18 citations
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization
2021 · 10 citations
Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence
2021 · 8 citations
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity
2022 · 8 citations
Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity
2022 · 8 citations
Softmax Policy Gradient Methods Can Take Exponential Time to Converge
2021 · 7 citations
Settling the Sample Complexity of Model-Based Offline Reinforcement Learning
2022 · 7 citations
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction
2020 · 5 citations
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting
2021 · 5 citations
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond
2023 · 4 citations
Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model
2022 · 3 citations
Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning
2023 · 3 citations
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning
2021 · 2 citations
Top co-authors
Yuxin Chen
· 13
Laixi Shi
· 11
Yuting Wei
· 10
Shicong Cen
· 8
Gen Li
· 4
Adam Wierman
· 3
Eric Mazumdar
· 3
Gen Li
· 3
Jiin Woo
· 3
Bo Dai
· 2
Dale Schuurmans
· 2
Gauri Joshi
· 2
Topics
Value-Based
Model-Based RL
Multi-Agent
Exploration
Offline RL
Game AI
Policy Gradient
RLHF & Alignment
Safe RL
Meta-RL