Prof. Wang Xizhao Invited to Give a Talk

Tititle: Learning from Uncertainty for Big Data 大數據在不確定性下的學習

Speaker: prof. Wang Xizhao

Date: 9th December 2016 (Friday)

Time: 11:00 to 13:00

Venue: A301

 

Abstract:

Big data refers to the datasets that are so large that conventional database management and data analysis tools are insufficient to work with them. Big data has become a bigger-than-ever problem with the quick developments of data collection and storage technologies. Model simplification is one of the most popular approaches to big data processing. After a brief tutorial of the existing techniques of processing big data, this talk will present some key issues of learning from big data with uncertainty, focusing on the impact of handling uncertainty on the model simplification. It shows that the representation, measure, and handling of the uncertainty have a significant influence on the performance of learning from big data. Some new advances in our Big Data Institute regarding the research on big data analysis and its applications to different domains are briefly introduced.  

 

Speaker:

Xizhao Wang (IEEE Fellow, 2013) is a processor in the Big Data Institute, College of Computer Science and Software Engineering, ShenZhen University. He received his PhD in computer science from Harbin Institute of Technology on September 1998. From 2000 to 2012 Dr. Wang served in Hebei University as a professor and the dean of school of Mathematics and Computer Sciences.

Prof. Wang’s major research interests include uncertainty modeling and machine learning for big data. Prof. Wang has edited 6+ special issues and published 3 monographs, 2 textbooks, and 150+ peer-reviewed research papers. Prof. Wang is on the list of Elsevier 2015 most cited Chinese authors. As a Principle Investigator (PI) or co-PI, Prof. Wang's has completed 30+ research projects.

Prof. Wang is an IEEE Fellow, the previous BoG member of IEEE SMC society, the chair of IEEE SMC Technical Committee on Computational Intelligence, the Chief Editor of Machine Learning and Cybernetics Journal, and an associate editor for a number of international journals.

 

2016120901

 

2016120902

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