学术报告第202129期

报告题目：Dealing with concept drift in stream data mining

报 告 人：Leszek Rutkowski, Czestochowa University of Technology, Poland

报告时间：2021年3月10日

报告地点：线上报告

Abstract: This lecture presents an overview of techniques to deal with concept drift in stream data mining, and moreover, describes original concepts developed by the author to solve classification and regression problems in a nonstationary environment. Unlike the vast majority of previous approaches, which are largely based on heuristics, it highlights methods and algorithms that are mathematically justified. More precisely, nonparametric techniques based on Parzen kernels and orthogonal series are employed to address concept drift in the problem of non-stationary regressions and classification in a time-varying environment. The content of the lecture will be beneficial for researchers and practitioners who deal with stream data, e.g. in telecommunication, banking, and sensor networks. The material presented in the lecture is based on the recent book:

Leszek Rutkowski, Maciej Jaworski, Piotr Duda, “Stream Data Mining: Algorithms and Their Probabilistic Properties”, Studies in Big Data, Springer 2020.

Biography:Professor Leszek Rutkowski (IEEE Fellow and Full Member of the Polish Academy of Sciences) received the M.Sc. degree in cybernetics, the Ph.D. and D.Sc. degrees in automatic control/learning systems from the Wrocław University of Technology, Wrocław, Poland, in 1977, 1980, and 1986, respectively, and the honoris causa degree from the AGH University of Science and Technology, Cracow, Poland, in 2014. He has been with the Czestochowa University of Technology, Czestochowa, Poland, since 1980, where he currently holds the position of a Full Professor. From 1987 to 1990, he held a visiting position with the School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK, USA. In 2004, he was elected as a member of the Polish Academy of Sciences, Warsaw, Poland. He has authored/co-authored over 300 publications and 8 books. Professor Leszek Rutkowski was a recipient of the IEEE Transaction on Neural Networks Outstanding Paper Award and, as the Chairman of the Chapter, the Outstanding Chapter Award from the IEEE Computational Intelligence Society. He was awarded by the IEEE Fellow Membership Grade for contributions to neurocomputing and flexible fuzzy systems in 2004. In 2015 Professor Leszek Rutkowski received a degree honoris causa from the prestigious AGH University of Science and Technology in Cracow “in recognition of outstanding scientific achievements in the field of artificial intelligence in particular neuro-fuzzy systems”. Professor Leszek Rutkowski is the Founding Chair of the Polish Chapter of the IEEE Computational Intelligence Society, and in 2019 was elected as the President of the Polish Neural Network Society. His current research interests include stream data mining, neural networks, deep learning, multiagent systems, fuzzy modeling, and pattern classification. He is editor-in-chief of the Journal of Artificial Intelligence and Soft Computing Research, and he is on the editorial board of the IEEE Transactions on Cybernetics, International Journal of Neural Systems, International Journal of Applied Mathematics and Computer Science and Knowledge and Information Systems. He is a widely cited and internationally recognized scholar with an H index equal to 52, 43, and 42, in Google Scholar, Web of Science, and Scopus databases, respectively.