I am a third-year Ph.D. student in Computer Science at University of Illinois Urbana-Champaign. My research interests lie in Machine Learning, including
Please find my CV here.
[Google Scholar]. * means equal contribution.
Robust Thompson Sampling Algorithms Against Reward Poisoning Attacks
Yinglun Xu, Zhiwei Wang , Gagandeep Singh
arXiv:2410.19705
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Binary Reward Labeling: Bridging Offline Preference and Reward-Based Reinforcement Learning
Yinglun Xu*, David Zhu*, Rohan Gumaste, Gagandeep Singh
arXiv:2406.10445
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Universal Black-Box Reward Poisoning Attack against Offline Reinforcement Learning
Yinglun Xu*, Rohan Gumaste*, Gagandeep Singh
arXiv:2402.09695
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Two-Step Offline Preference-Based Reinforcement Learning with Constrained Actions
Yinglun Xu, Tarun Suresh, Rohan Gumaste, David Zhu, Ruirui Li, Zhengyang Wang, Haoming Jiang, Xianfeng Tang, Qingyu Yin, Monica Xiao Cheng, Qi Zeng, Chao Zhang, Gagandeep Singh
arXiv:2401.00330
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Efficient Reward Poisoning Attacks on Online Deep Reinforcement Learning
Yinglun Xu, Qi Zeng, Gagandeep Singh
Transactions on Machine Learning Research (TMLR)
[PDF] [Code]
On the robustness of epsilon greedy in multi-agent contextual bandit mechanism
Yinglun Xu, Bhuvesh Kumar, Jacob Abernethy
arXiv:2307.07675
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Black-Box Targeted Reward Poisoning Attack Against Online Deep Reinforcement Learning
Yinglun Xu, Gagandeep Singh
arXiv:2305.10681
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Single-molecule optofluidic microsensor with interface whispering gallery modes
Xiao-Chong Yu, Shui-Jing Tang, Wenjing Liu, Yinglun Xu, Qihuang Gong, You-Ling Chen, Yun-Feng Xiao
PNAS 2022 (Proceedings of the National Academy of Sciences)
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Thin-film optical parametric oscillators
Alireza Marandi, Luis Ledezma, Yinglun Xu, Ryan Briggs
US Patent 2022
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Observation-Free Attacks on Stochastic Bandits
Yinglun Xu, Bhuvesh Kumar, Jacob Abernethy
NeurIPS 2021
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Adversarial Attack and Robust Learning in Multi-Arm Bandit Problems
Yinglun Xu
M.S. Thesis
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