时间：2017-4-5,15:40

地点：长安校区图书馆一层西附楼会议室

主办单位：永利yl23411、图书馆

报告人：Witold Pedrycz，加拿大阿尔伯塔大学教授、院士

报告题目：Data Analytics: Selected Insights into Data Quality, Associations, and Information Granules

Abstract

Data are the blood life of today’s society.  The diversity of data is enormous. The quality of data including their comprehensive and multifaceted characterization becomes of paramount importance and is central to further data analysis and processing.

In this presentation, we cover a suite of selected insights into data quality and elaborate on their quantification. The two central issues involving coping with incomplete data (invoking data imputation) and imbalanced data are discussed.

In addressing these issues and delivering algorithmically sound solutions, we advocate a central role of information granularity being played in dealing with the two above stated problems and yielding the results quantified in terms of information granules.

Revealing interpretable and conceptually stable associations (relationships) within data form another central item on the agenda of data analytics. We show how granular mappings engaging granular parameter spaces are developed and assessed.  Associative relationships constructed in terms of granular bidirectional and multidirectional associative memories are investigated. We also develop granular autoencoders and stacked granular autoencoders.

Biography

Witold Pedrycz is Professor and Canada Research Chair (CRC) in Computational Intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland. He is a foreign member of the Polish Academy of Sciences, and a Fellow of the Royal Society of Canada, IEEE, and IFSA. He is a recipient of numerous awards including a prestigious Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Society, IEEE Canada Computer Engineering Medal, Cajastur Prize for Soft Computing, Killam Prize, and a Fuzzy Pioneer Award from the IEEE Computational Intelligence Society.

His main research directions involve Computational Intelligence, fuzzy modeling and Granular Computing, knowledge discovery and data mining, fuzzy control, pattern recognition, knowledge-based neural networks, relational computing, and Software Engineering. He is an author of 15 research monographs covering various aspects of Computational Intelligence, data mining, and Software Engineering.

Dr. Pedrycz is intensively involved in editorial activities. He is an Editor-in-Chief of Information Sciences and Editor-in-Chief of WIREs Data Mining and Knowledge Discovery (Wiley).  He currently serves as an Associate Editor of IEEE Transactions on Fuzzy Systems and is a member of a number of editorial boards of other international journals.