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Poster
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Wed 15:30
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A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes
Chengchun Shi · Masatoshi Uehara · Jiawei Huang · Nan Jiang
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Poster
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Thu 15:00
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From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses
Daniil Tiapkin · Denis Belomestny · Eric Moulines · Alexey Naumov · Sergey Samsonov · Yunhao Tang · Michal Valko · Pierre Menard
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Poster
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Wed 15:30
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Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits
Qinghua Liu · Yuanhao Wang · Chi Jin
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Spotlight
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Wed 10:25
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Expression might be enough: representing pressure and demand for reinforcement learning based traffic signal control
Liang Zhang · Qiang Wu · Jun Shen · Linyuan Lü · Bo Du · Jianqing Wu
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Poster
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Thu 15:00
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Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach
Xuezhou Zhang · Yuda Song · Masatoshi Uehara · Mengdi Wang · Alekh Agarwal · Wen Sun
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Spotlight
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Thu 11:40
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Provably Efficient Offline Reinforcement Learning for Partially Observable Markov Decision Processes
Hongyi Guo · Qi Cai · Yufeng Zhang · Zhuoran Yang · Zhaoran Wang
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Spotlight
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Wed 7:50
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The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces
Chi Jin · Qinghua Liu · Tiancheng Yu
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Spotlight
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Thu 11:50
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Lagrangian Method for Q-Function Learning (with Applications to Machine Translation)
Huang Bojun
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Poster
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Thu 15:00
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Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity
Laixi Shi · Gen Li · Yuting Wei · Yuxin Chen · Yuejie Chi
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Poster
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Thu 15:00
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An Analytical Update Rule for General Policy Optimization
Hepeng Li · Nicholas Clavette · Haibo He
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Spotlight
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Wed 10:25
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Cascaded Gaps: Towards Logarithmic Regret for Risk-Sensitive Reinforcement Learning
Yingjie Fei · Ruitu Xu
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Spotlight
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Wed 14:55
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Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation
Aivar Sootla · Alexander I Cowen-Rivers · Taher Jafferjee · Ziyan Wang · David Mguni · Jun Wang · Haitham Bou Ammar
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