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Poster
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Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation
Dan Qiao · Yu-Xiang Wang
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Poster
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Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian
Paria Rashidinejad · Hanlin Zhu · Kunhe Yang · Stuart Russell · Jiantao Jiao
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Poster
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Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks
Xiang Ji · Minshuo Chen · Mengdi Wang · Tuo Zhao
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Poster
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A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
Zixiang Chen · Chris Junchi Li · Angela Yuan · Quanquan Gu · Michael Jordan
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Poster
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Wed 7:30
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Provably Efficient Risk-Sensitive Reinforcement Learning: Iterated CVaR and Worst Path
Yihan Du · Siwei Wang · Longbo Huang
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Poster
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Tue 2:30
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Provable Sim-to-real Transfer in Continuous Domain with Partial Observations
Jiachen Hu · Han Zhong · Chi Jin · Liwei Wang
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Poster
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Wed 2:30
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Hybrid RL: Using both offline and online data can make RL efficient
Yuda Song · Yifei Zhou · Ayush Sekhari · Drew Bagnell · Akshay Krishnamurthy · Wen Sun
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Poster
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The Role of Coverage in Online Reinforcement Learning
Tengyang Xie · Dylan Foster · Yu Bai · Nan Jiang · Sham Kakade
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Poster
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Wed 7:30
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Efficiently Computing Nash Equilibria in Adversarial Team Markov Games
Fivos Kalogiannis · Ioannis Anagnostides · Ioannis Panageas · Emmanouil-Vasileios Vlatakis-Gkaragkounis · Vaggos Chatziafratis · Stelios Stavroulakis
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Oral
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Wed 6:10
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Efficiently Computing Nash Equilibria in Adversarial Team Markov Games
Fivos Kalogiannis · Ioannis Anagnostides · Ioannis Panageas · Emmanouil-Vasileios Vlatakis-Gkaragkounis · Vaggos Chatziafratis · Stelios Stavroulakis
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Poster
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Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game
Wei Xiong · Han Zhong · Chengshuai Shi · Cong Shen · Liwei Wang · Tong Zhang
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Poster
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Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-Free RL
Ruiquan Huang · Jing Yang · Yingbin Liang
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