Xiaoyu Chen

I am Ph.D. student in at IIIS, Tsinghua University, I am fortunate to be advised by Prof. Jianyu Chen, and work closely with Dr. Li Zhao at Microsoft Research.

Prior to that, I received dual bachelor's degrees in Computer Science and Technology and Economics (second degree) from Tsinghua University. My research has been recognized with awards including outstanding graduate student honors, outstanding undergraduate thesis award, and a national scholarship.

Email / Scholar

	An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu NeurIPS 2022 A new RL method (SeCBAD) for handling real-world situations where the environment changes abruptly within an episode , allowing agents to adapt to these context variations.
	Flow-based Recurrent Belief State Learning for POMDPs Xiaoyu Chen, Yao Mu, Ping Luo, Shengbo Li, Jianyu Chen ICML 2022 (Outstanding Undergraduate Thesis Award) A new method (FORBES) for learning general continuous belief states in POMDPs, enhances the performance of downstream RL algorithms by reducing approximation errors during state inference.
	Distributional Reinforcement Learning for Multi-Dimensional Reward Functions Pushi Zhang, Xiaoyu Chen*, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu NeurIPS 2021* Model the joint return distribution across multiple reward sources in distributional RL, capturing both inherent randomness and rich correlations.
	Towards Generalizable Reinforcement Learning for Trade Execution Chuheng Zhang, Yitong Duan, Xiaoyu Chen, Jianyu Chen, Jian Li, Li Zhao IJCAI 2023 Investigate and mitigate overfitting issues that arise when applying reinforcement learning to optimized trade execution.
	Noisy Agents: Self-supervised Exploration by Predicting Auditory Events Chuang Gan, Xiaoyu Chen, Phillip Isola, Antonio Torralba, Joshua B. Tenenbaum IROS 2022 A novel type of intrinsic motivation that encourages the agent to understand the causal effect of its actions through auditory event prediction.
	Certifiably Robust Interpretation via Renyi Differential Privacy Ao Liu, Xiaoyu Chen, Sijia Liu, Lirong Xia, Chuang Gan AAAI 2023 journal track A new interpretation method for convolutional neural networks (CNNs) based on Rényi differential privacy.

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