报 告 人：Professor Jie Lu
University of Technology, Sydney (UTS), Australia
邀 请 人：骆祥峰 教授，岳晓冬 副教授
Concept Drift is known as unforeseeable change in underlying streaming data distribution over time. The phenomenon of concept drift has been recognized as the root cause of decreased effectiveness in many decision-related applications. Adaptive learning under concept drift is a relatively new research field and is one of the most pressing and fundamental problems in the current age of big data. Building an adaptive system is a highly promising solution for coping with persistent environmental change and avoiding system performance degradation. This talk will present a set of methods and algorithms that can effectively and accurately detect concept drift, understand and react to it, with knowledge adaptation, in a timely way.
Jie Lu is a distinguished professor and an internationally renowned scientist in the areas of computational intelligence, specifically in decision support systems, fuzzy transfer learning, concept drift, and recommender systems. She is the Associate Dean in Research Excellence in the Faculty of Engineering and Information Technology at University of Technology Sydney (UTS) and the Director of Centre for Artificial Intelligence (CAI) at UTS. She has published six research books and 400 papers in Artificial Intelligence, IEEE transactions on Fuzzy Systems and other refereed journals and conference proceedings. She has won 8 Australian Research Council (ARC) discovery grants and many other research grants. She serves as Editor-In-Chief for Knowledge-Based Systems (Elsevier) and Editor-In-Chief for International Journal on Computational Intelligence Systems (Atlantis), has delivered 20 keynote speeches at international conferences, and has chaired 10 international conferences. She is a Fellow of IEEE and Fellow of IFSA.