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【海韵讲座】2019年第89期-Metric learning with Lipschitz continuous functions
发布时间:2019年12月23日 浏览次数:

海韵讲座第89

报告题目Metric learning with Lipschitz continuous functions

主讲人Dr Jing-Hao Xue, Associate Professor, Department of Statistical Science, University College London (UCL)

时间2019122510:00-11:00

地点:海韵园行政楼C505

报告简介

Metric learning enables classification algorithms to automatically learn a suitable distance metric from data, such that semantically similar instances are pulled together while dissimilar instances are pushed away. A learned metric can significantly improve the performance of distance-based classifiers (e.g. kNN). In this talk, I will briefly present some of our recent research efforts on metric learning with Lipschitz continuous functions, including methodology, theoretical foundation and optimisation formulation of each work. A brief introduction to University College London (UCL) will also be given.

报告人简介

Dr Jing-Hao Xue received a BEng degree in telecommunication and information systems in 1993 and a DrEng degree in signal and information processing in 1998, both from Tsinghua University. He received an MSc degree in medical imaging and an MSc degree in statistics, both from Katholieke Universiteit Leuven in 2004, and a PhD degree in statistics from the University of Glasgow in 2008. He is an Associate Professor in the Department of Statistical Science at University College London (UCL) and a Turing Fellow in the Alan Turing Institute. His research interests include statistical machine learning, high-dimensional data analysis, statistical pattern recognition and image analysis.

Jing-Hao Xue博士分别于1993年和1998年在清华大学电子工程系获通信与信息系统学士和信号与信息处理博士,2004年在比利时鲁汶大学获医学成像硕士和统计学硕士,2008年在英国格拉斯哥大学获统计学博士。现为英国伦敦大学学院(UCL)统计科学系副教授和阿兰图灵研究所图灵学者(Turing Fellow)。研究兴趣主要是统计机器学习,高维数据分析,统计模式识别和图像分析。

邀请人:严严 计算机系

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