题目: Regularized Incremental Linear Discriminant Analysis on Large-Scale Data

　　时间：2018年7月3日，10：30-11：30

　　地点：理学院206

　　报告人：储德林教授（新加坡国立大学）

　　Abstract:  Over the past few decades, a lot of attention has been drawn to large-scale streaming data analysis, where researchers are faced with huge amount of high-dimensional data acquired in a stream fashion. In this case, conventional algorithms that compute the result from scratch whenever a new data comes are highly inefficient. To handle this problem, we propose a new incremental regularized least squares algorithm that is applied to supervised dimensionality reduction of large-scale streaming data with focus on linear discriminant analysis.  Experimental results on real-world data sets demonstrate the effectiveness and efficiency of our algorithms.

　　报告人简介：新加坡国立大学教授。于清华大学获得学士、硕士、博士学位。先后在香港大学、清华大学、德国TU Chemnitz、University of Bielefeld等高校工作过。主要研究领域是科学计算、数值代数及其应用，在SIAM系列杂志、Numerische Mathematik, Mathematics of Computation, IEEE. Trans. PAMI, Automatica等国际知名学术期刊发表论文一百余篇。任Automatica期刊的副主编，Journal of Computational and Applied Mathematics的顾问编委，Journal of the Franklin Institute期刊的客座编委。