讲座人： Qiang Sun教授，University of Toronto

讲座题目：Adaptive Robust Regression

讲座时间：2020年10月21日，星期三，10:00-12:00

讲座简介：

Data are often contaminated by outliers. Classical robust regression methods introduce robustness by sacrificing statistical accuracy and efficiency, which is less desirable. In this talk, we discuss our recent work on adaptive robust regression methods, which simultaneously achieve robustness, asymptotic unbiasedness and full asymptotic efficiency. The key idea is that the robustification parameter should diverge to infinity in a data-dependent manner. We focus on two adaptive robust regression methods which are the adaptive versions of the classical Huber regression and the redescending regression. We examine the performances of these methods both theoretically and numerically. We also discuss other possible applications and extensions.

讲座人简介：

Qiang Sun is an Assistant Professor of Statistics at Toronto. He received my PhD from University of North Carolina at Chapel Hill (UNC-CH) in 2014, and my BS from University of Science and Technology of China (USTC) in 2010. Qiang Sun is interested in mathematics and practice of data science, broadly defined. His recent research is driven by challenges in imaging sciences and operations research, and involves statistics, learning, optimization, information theory and probability theory. He views all these above as parts of modern statistics. He is also interested in the interaction between statistics and engineering.

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会议时间：2020/9/23 10:00-12:00

重复周期：每周(周三)

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