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Poster
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Tue 9:00
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Provably sample-efficient RL with side information about latent dynamics
Yao Liu · Dipendra Misra · Miro Dudik · Robert Schapire
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Poster
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Thu 14:00
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Provably Efficient Model-Free Constrained RL with Linear Function Approximation
Arnob Ghosh · Xingyu Zhou · Ness Shroff
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Poster
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Wed 14:00
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Sample-Efficient Reinforcement Learning of Partially Observable Markov Games
Qinghua Liu · Csaba Szepesvari · Chi Jin
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Poster
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Thu 14:00
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Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems
Masatoshi Uehara · Ayush Sekhari · Jason Lee · Nathan Kallus · Wen Sun
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Poster
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Wed 9:00
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A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation
Philip Amortila · Nan Jiang · Dhruv Madeka · Dean Foster
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Poster
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Tue 14:00
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Provable Benefit of Multitask Representation Learning in Reinforcement Learning
Yuan Cheng · Songtao Feng · Jing Yang · Hong Zhang · Yingbin Liang
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Poster
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Thu 9:00
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Theoretically Provable Spiking Neural Networks
Shao-Qun Zhang · Zhi-Hua Zhou
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Workshop
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Hybrid RL: Using both offline and online data can make RL efficient
Yuda Song · Yifei Zhou · Ayush Sekhari · J. Bagnell · Akshay Krishnamurthy · Wen Sun
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Poster
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Wed 14:00
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A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits
Jiafan He · Tianhao Wang · Yifei Min · Quanquan Gu
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Poster
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Tue 14:00
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Provably Efficient Offline Multi-agent Reinforcement Learning via Strategy-wise Bonus
Qiwen Cui · Simon Du
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Workshop
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Fri 13:30
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Hybrid RL: Using Both Offline and Online Data Can Make RL Efficient (Wen Sun)
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Poster
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Thu 9:00
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Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning
Dingwen Kong · Lin Yang
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