Distributed bandit learning: Near-optimal regret with efficient communication Y Wang, J Hu, X Chen, L Wang arXiv preprint arXiv:1904.06309, 2019 | 92 | 2019 |
Understanding domain randomization for sim-to-real transfer X Chen, J Hu, C Jin, L Li, L Wang arXiv preprint arXiv:2110.03239, 2021 | 65 | 2021 |
Near-optimal representation learning for linear bandits and linear rl J Hu, X Chen, C Jin, L Li, L Wang International Conference on Machine Learning, 4349-4358, 2021 | 46 | 2021 |
Efficient reinforcement learning in factored mdps with application to constrained rl X Chen, J Hu, L Li, L Wang arXiv preprint arXiv:2008.13319, 2020 | 21 | 2020 |
Near-optimal reward-free exploration for linear mixture mdps with plug-in solver X Chen, J Hu, LF Yang, L Wang arXiv preprint arXiv:2110.03244, 2021 | 17 | 2021 |
Provable sim-to-real transfer in continuous domain with partial observations J Hu, H Zhong, C Jin, L Wang arXiv preprint arXiv:2210.15598, 2022 | 6 | 2022 |
Provably efficient exploration in quantum reinforcement learning with logarithmic worst-case regret H Zhong, J Hu, Y Xue, T Li, L Wang arXiv preprint arXiv:2302.10796, 2023 | 1 | 2023 |
On Limitation of Transformer for Learning HMMs J Hu, Q Liu, C Jin arXiv preprint arXiv:2406.04089, 2024 | | 2024 |
Quantum Non-Identical Mean Estimation: Efficient Algorithms and Fundamental Limits J Hu, T Li, X Wang, Y Xue, C Zhang, H Zhong arXiv preprint arXiv:2405.12838, 2024 | | 2024 |
ZeroSwap: Data-driven Optimal Market Making in DeFi V Nadkarni, J Hu, R Rana, C Jin, S Kulkarni, P Viswanath arXiv preprint arXiv:2310.09413, 2023 | | 2023 |