Learning Bregman distance functions for semi-supervised clustering
Learning distance functions with side information plays a key role in many data mining applications. Conventional distance metric learning approaches often assume that the target distance function is represented in some form of Mahalanobis distance. These approaches usually work well when data are i...
محفوظ في:
المؤلفون الرئيسيون: | Wu, Lei, HOI, Chu Hong, Jin, Rong, Zhu, Jianke, Yu, N. |
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التنسيق: | text |
اللغة: | English |
منشور في: |
Institutional Knowledge at Singapore Management University
2012
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الموضوعات: | |
الوصول للمادة أونلاين: | https://ink.library.smu.edu.sg/sis_research/2282 https://ink.library.smu.edu.sg/context/sis_research/article/3282/viewcontent/Learning_Bregman_Distance_Functions_with_Applications_to_Semi_Supervised_Clustering.pdf |
الوسوم: |
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المؤسسة: | Singapore Management University |
اللغة: | English |
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