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Growing and Pruning Selective Ensemble Regression over Drifting Data Streams

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报告题目:Growing and Pruning Selective Ensemble Regression over Drifting Data Streams

报告人:Sheng Chen教授(英国University of Southampton、英国皇家工程院院士、IEEE FELLOW)

时间: 2019年7月22日(周一)上午10:40

地点:1066vip威尼斯宝山校区东区9号机自大楼604室

报告摘要:

From my ‘made-up famous’ equation AI =ed _ C2, whereedstands for our electronic

and digital infrastructure andC2 equals to Computing and Communication, I’ll start a light-hearted history of how AI is saved at least partly by ‘Computation Intelligence’ or CI – which is the theme of my talk. More specifically, my talk is about how to adaptively construct online selective ensemble regression model for fast-arriving highly nonlinear and nonstationary data streams. Any ensemble learner faces a so-called stability-plasticity dilemma. Stability implies that a learner retains acquired knowledge for maintaining diverse pool of past knowledge, but plasticity requires a learner to forget part or all previous knowledge so that it can quickly capture new knowledge from newly upcoming data. We propose a growing and pruning selective ensemble regression for adaptive modeling of nonlinear and nonstationary systems. Central to this effective and accurate selective ensemble learner is its growing strategy and pruning strategy. During online operation, the proposed growing strategy automatically identifie newly emerging process state and fits a local linear model to capture this newly occurring knowledge. Therefore, our learning strategy is capable of maintaining the maximum diversity of the base model set. Furthermore, our proposed pruning strategy is capable of reliably removing ‘unwanted’ local models online and, therefore, significantly reduces computational complexity of constructing online selective ensemble regression model, without sacrificing the diversity and accuracy of selective ensemble regression.

报告人简介:

Sheng Chen received the BEng degree from East China Petroleum Institute (now China University of Petroleum), China, in January 1982, and the PhD degree from City University, London, in September 1986, both in control engineering. In 2005, he was awarded the higher doctoral degree, Doctor of Science (DSC), by the University of Southampton. From October 1986 to August 1999, he held various research and academic posts with University of Sheffield, University of Edinburgh and University of Portsmouth, all in UK. Since September, 1999, he has been with School of Electronics and Computer Science, University of Southampton, where he holds the post of Professor in Intelligent Systems and Signal Processing. Professor Chen’s research interests are in computation intelligence, wireless communications and signal

processing. He has 13,100 plus Web of Science citations with h-index 50, and 27,400 plus Google Scholar citations with h-index 71. Dr Chen is a Fellow of the United Kingdom Royal Academy of Engineering, a fellow of IEEE and a fellow of IET. He is one of the original ISI most highly cited researchers in engineering (March 2004).

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