Learning under Concept Drift

活动时间： 12月01日15时00分       

地            点  ： 理科群1号楼D-203室

讲座内容：

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 and react to it, with knowledge adaptation, in a timely way.  

主讲人介绍：

Distinguished Professor Jie Lu is an internationally established scientist in the areas of fuzzy transfer learning, decision support systems, concept drift, recommender systems, prediction and early warning systems. She is the Associate Dean in Research Excellence in the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS). She is also the Director of the Centre for Artificial Intelligence (CAI). She has published six research books and more than 400 papers in refereed journals and conference proceedings. She has won eight Australian Research Council (ARC) discovery grants and 10 other research grants in the last 15 years. She serves as Editor-In-Chief for Knowledge-Based Systems (Elsevier) and as Editor-In-Chief for International Journal on Computational Intelligence Systems (Atlantis), has delivered about 20 keynote speeches at international conferences, and has chaired 10 international conferences. She is an ARC panel member (2016-2018), IEEE Fellow (in computational intelligence) and IFSA (International Fuzzy System Association) Fellow.

发布时间：2017-11-30 08:09:18