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學術講座

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2020年1月3日學術報告(薛景浩 教授,倫敦大學學院 )
2020年01月02日16時 人評論

報告題目:Metric learning with Lipschitz continuous functions

報告時間:2020年1月3日(周五)上午10:30

報告地點:計算機學院B403會議室

報告人:薛景浩

報告人單位:倫敦大學學院

報告人簡介: 

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.

報告摘要:

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.

邀請人張樂飛 教授

 


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