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2020年1月3日学术报告(薛景浩 教授,伦敦大学学院 )
2020年01月02日16时 人评论

报告题目:Metric learning with Lipschitz continuous functions

报告时间:2020年1月3日(周五)上午10:30

报告地点:网赌最佳平台B403会议室

报告人:薛景浩

报告人单位:伦敦大学学院

报告人简介: 

Dr Jing-Hao Xue received a BEng degree in telecommunication and information systems in 1993 and a Dr Eng 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.

报告摘要:

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.

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