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Research
Currently, I am mainly working on user modeling and sequential recommendation with applications where users' inherent states are not observable from partially observed data. The title of my working thesis is "Sequential User Modeling and Recommendation Under Partially Obeservable Environment". I am also working on counterfactual evaluation and model-based reinforcement learning that are related to offline evaluation of long-term and delayed rewards of sequential recommendation policies. Besides, I am also interested in and have been working on anomaly pattern detection in images and graphs. Overall, I have 6 years hand-on experience on doing research independently and collaboratively, including identifing the nature of a problem, conducting literurature reviews, statistical modeling, rigorous experimental design and result analysis. Following is a list of my publications.
研究兴趣
论文共 13 篇作者统计合作学者相似作者
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PROCEEDINGS OF THE 32ND ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, CIKM 2023pp.2616-2625, (2023)
arxiv(2023)
ACM Conference on Recommender Systems (RecSys) (2022)
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