2010年12月27日，应中国科学技术大学计算机学院的邀请，机器学习等领域知名专家、德克萨斯大学奥斯汀分校Huan Xu博士在计算机学院学术报告厅作了题为 《High-Dimensional Robust PCA》的专题报告。报告会由计算机学院徐林莉副教授主持。
Huan Xu博士正在作报告
Huan Xu博士首先通过具体实例向同学们展现了目前数据已经走向高维化，对传统的方法以及统计技术提出了新的挑战。他针对普通的PCA算法对损坏点的高度敏感性，不适用于存在一定比例的观察数据会被任意损坏的高维数据的特点，提出了一种高维鲁棒性的PCA（HR-PCA）算法。HR-PCA算法是第一个适用在高维数据的鲁棒性PCA算法。报告图文并茂，在严密推理和证明下，将该算法具有可计算性、对污点的鲁棒性、易核化等优点清晰地呈现出来，并结合实际数据评价了该方法。报告引起了同学们强烈的兴趣，在报告中同学们与Huan Xu博士展开了热烈的讨论。
报告会现场
附录：
Huan Xu is a postdoctoral associate in the Department of Electrical and Computer Engineering at The University of Texas at Austin. He received the B.Eng. degree in automation from Shanghai Jiaotong University, Shanghai, China in 1997, the M.Eng. degree in electrical engineering from the National University of Singapore in 2003, and the Ph.D. degree in electrical engineering from McGill University, Canada in 2009. His research interests include high-dimensional data analysis, machine learning, robust optimization, and decision making and control under uncertainty. Starting from Jan. 2011, he will join the Department of Mechanical Engineering of the National University of Singapore as an Assistant Professor.
