Abstract
This paper presents an algorithm which learns a distance metric from a data set by knowledge embedding and uses the new distance metric to solve nonlinear pattern recognition problems such a clustering.
Original language | English |
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Pages (from-to) | 161-163 |
Number of pages | 3 |
Journal | Pattern Recognition |
Volume | 37 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2004 |
Keywords
- Clustering
- Distance metric learning
- Knowledge embedding
ASJC Scopus subject areas
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence