Prof. Feiping Nie
Date and Time:
9:00 – 10:00 am, Friday, May 8, 2017.
Room 146 Research Building
Large Graph Learning: Methodology and Application
Graph based methods are popular and effective to solve many machine learning problem. However, traditional graph based methods are very time-consuming, which make them difficult to be applied in large scale data. In big data era, it is important and urgent to accelerate the graph based methods and make them scalable to big data. In this talk, I will introduce a new and effective large graph construction approach. This approach is linear time to the number of data points and thus can be applied in the case with million data. I will also discuss how to apply this approach to accelerate many graph based machine learning methods.
聂飞平，西北工业大学教授、博士生导师，2015年入选中组部青年千人计划。主要研究兴趣为模式识别与机器学习中的理论和方法设计，并将所设计的方法成功应用于图像分割与标注、多媒体信息理解与检索、生物信息学等多个领域的实际问题中。已在PAMI、IJCV、Bioinformatics、ICML、NIPS、SIGKDD等国际顶尖期刊和会议上发表学术论文200余篇，其中在中国计算机学会（CCF）推荐的A类期刊和会议上发表论文100余篇。据Google Scholar统计，论文总引用为6000余次，H指数为44。常年应邀担任相关领域顶级期刊和会议的审稿专家或程序委员会委员，并同时应邀担任IEEE Transactions on Neural Networks and Learning Systems、Information Science等多个国际一流SCI期刊的编委。