Wenlong Mou is an Assistant Professor in the Department of Statistical Sciences at University of Toronto. In 2023, he received his Ph.D. degree in Electrical Engineering and Computer Sciences (EECS) from UC Berkeley. Prior to Berkeley, he received his B.Sc. degree in Computer Science and B.A. degree in Economics, both from Peking University. Wenlong's research interests include machine learning theory, mathematical statistics, optimization, and applied probability. He is particularly interested in designing optimal statistical methods that enable optimal data-driven decision making, powered by efficient computational algorithms. His works have been published in many leading journals in the area of statistical machine learning. His research has been recognized by the INFORMS Applied Probability Society as a Best Student Paper finalist.
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日期 | 时间 | 会场 | Session | 角色 | 讲题 |
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2025-07-13 | 13:30-13:50 | B会议室 Meeting Room B |
CS037: Advances in Deep Learning Architectures and Applications CS037: Advances in Deep Learning Architectures and Applications |
贡献报告 Contributed Talk | Fine-tuning diffusion processes with function approximations: a PDE learning approachFine-tuning diffusion processes with function approximations: a PDE learning approach |