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学术沙龙:Evidential Machine learning
文:人力资源部教师发展中心 来源:机电学院 党委教师工作部、人力资源部 时间:2021-06-21 1406

  本期学术沙龙将邀请法国贡比涅大学Thierry Denoeux教授与大家进行深度交流和探讨,欢迎广大师生积极参与!

  一、主 题Evidential Machine learning

  二、主讲人:法国贡比涅大学 Thierry Denoeux 教授

  三、时 间:2021年6月23日(周三)16:00-18:00

  四、参会方式:腾讯会议  会议ID:462 436 470

  五、主持人:刘宇 教授

  六、内容简介:

  The theory of belief functions is a general framework for reasoning and making decisions based on uncertain information. Belief functions are grounded in the theory of random sets and can be seen both as generalized sets and as nonadditive probability measures. The topic of this talk is evidential machine learning, defined as machine learning based on belief functions. We show how this approach makes it possible to quantify prediction uncertainty in supervised or partially supervised learning, and how it allows us to extract richer knowledge from data using the concept of evidential clustering. Recent connections with deep learning are discussed.

  七、主讲人简介:

  Thierry Denoeux is a Full Professor (Exceptional Class) with the Department of Information Processing Engineering at the University of Compiègne, France, and a senior member of the French Academic Institute (Institut Universitaire de France). His research interests concern reasoning and decision-making under uncertainty and, more generally, the management of uncertainty in intelligent systems. His main contributions are in the theory of belief functions with applications to statistical inference, pattern recognition, machine learning and information fusion. He has published more than 300 papers in this area. He is the Editor-in-Chief of the International Journal of Approximate Reasoning', and an Associate Editor of several journals including Fuzzy Sets and Systems.

  八、主办单位:人力资源部教师发展中心

    承办单位:机械与电气工程学院


                     人力资源部教师发展中心

                       2021年6月21日


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