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...
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Main Authors: | , , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2013
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/84506 http://hdl.handle.net/10220/13469 |
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Institution: | Nanyang Technological University |
Language: | English |