Publications

Yingru Li (2024). Simple, unified analysis of Johnson-Lindenstrauss with applications. The 37th Annual Conference on Learning Theory (COLT) (Submitted).

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Yingru Li, Zhi-Quan Luo (2024). Prior-dependent analysis of posterior sampling reinforcement learning with function approximation. The 27th International Conference on Artificial Intelligence and Statistics (AISTATS).

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Yingru Li, Liangqi Liu, Wenqiang Pu, Zhi-Quan Luo (2024). Optimistic Thompson Sampling for No-Regret Learning in Unknown Games. The 41st International Conference on Machine Learning (ICML) (Submitted).

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Yingru Li, Jiawei Xu, Lei Han, Zhiquan Luo (2024). HyperAgent: A Simple, Scalable, Efficient and Provable Reinforcement Learning Framework for Complex Environments. The 41st International Conference on Machine Learning (ICML) (Submitted).

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Yingru Li, Jiawei Xu, Zhiquan Luo (2023). Efficient and scalable reinforcement learning via hypermodel. NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in the Real World.

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Ziniu Li, Yingru Li, Yushun Zhang, Tong Zhang, Zhi-Quan Luo (2022). HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning. International Conference on Learning Representations (ICLR).

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Qing Wang, Yingru Li, Jiechao Xiong, Tong Zhang (2019). Divergence-augmented policy optimization. Advances in Neural Information Processing Systems.

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