学术信息

2018系列学术报告之十三

来源: 发布日期:2018-06-20


题  目: Regularized Incremental Linear Discriminant Analysis  on Large-Scale Data

报告人:储德林教授,新加坡国立大学

时  间:2018年6月22日    9:30-10:30

地  点:3-309

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.


报告人概况:

储德林,新加坡国立大学教授。1982年考入清华大学,获学士、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.,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。