李落清教授學術報告會

發布時間:9号彩票捷豹平台10-21

報告題目:Atomic Representation-based Classification: Algorithm and Theory

報 告 人:李落清 教授(湖北大學)

報告時間:20191022日(星期二)上午1030

報告地點:磬苑校區理工D318

主辦單位:安徽大學計算機科學與技術學院

歡迎各位老師、同學屆時前往!

                                         

科學技術處

                                       20191021

 

報告摘要:

Representation-based classification (RC) methods such as sparse RC (SRC) have attracted great interest in pattern recognition recently. In this talk, we introduce a new condition called atomic classification condition (ACC), which reveals important geometric insights for the theory of ARC. We establish the theoretical guarantees for a general unified framework termed as atomic representation-based classification (ARC), which includes most RC methods as special cases. We show that under such condition ARC is provably effective in correctly recognizing any new test sample, even corrupted with noise. Numerical results are provided to validate and complement our theoretical analysis of ARC and its important special cases for both noiseless and noisy test data.

 


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