Exploiting side information in locality preserving projection
Even if the class label information is unknown, side information represents some equivalence constraints between pairs of patterns, indicating whether pairs originate from the same class. Exploiting side information, we develop algorithms to preserve both the intra-class and inter-class local struct...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
IEEE
2008
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| Online Access: | http://hdl.handle.net/20.500.11937/30673 |
| _version_ | 1848753154815950848 |
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| author | An, Senjian Liu, Wan-Quan Venkatesh, Svetha |
| author2 | NA |
| author_facet | NA An, Senjian Liu, Wan-Quan Venkatesh, Svetha |
| author_sort | An, Senjian |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Even if the class label information is unknown, side information represents some equivalence constraints between pairs of patterns, indicating whether pairs originate from the same class. Exploiting side information, we develop algorithms to preserve both the intra-class and inter-class local structures. This new type of locality preserving projection (LPP), called LPP with side information (LPPSI), preserves the datapsilas local structure in the sense that the close, similar training patterns will be kept close, whilst the close but dissimilar ones are separated. Our algorithms balance these conflicting requirements, and we further improve this technique using kernel methods. Experiments conducted on popular face databases demonstrate that the proposed algorithm significantly outperforms LPP. Further, we show that the performance of our algorithm with partial side information (that is, using only small amount of pair-wise similarity/dissimilarity information during training) is comparable with that when using full side information. We conclude that exploiting side information by preserving both similar and dissimilar local structures of the data significantly improves performance. |
| first_indexed | 2025-11-14T08:20:01Z |
| format | Conference Paper |
| id | curtin-20.500.11937-30673 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:20:01Z |
| publishDate | 2008 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-306732018-03-29T09:08:00Z Exploiting side information in locality preserving projection An, Senjian Liu, Wan-Quan Venkatesh, Svetha NA Even if the class label information is unknown, side information represents some equivalence constraints between pairs of patterns, indicating whether pairs originate from the same class. Exploiting side information, we develop algorithms to preserve both the intra-class and inter-class local structures. This new type of locality preserving projection (LPP), called LPP with side information (LPPSI), preserves the datapsilas local structure in the sense that the close, similar training patterns will be kept close, whilst the close but dissimilar ones are separated. Our algorithms balance these conflicting requirements, and we further improve this technique using kernel methods. Experiments conducted on popular face databases demonstrate that the proposed algorithm significantly outperforms LPP. Further, we show that the performance of our algorithm with partial side information (that is, using only small amount of pair-wise similarity/dissimilarity information during training) is comparable with that when using full side information. We conclude that exploiting side information by preserving both similar and dissimilar local structures of the data significantly improves performance. 2008 Conference Paper http://hdl.handle.net/20.500.11937/30673 10.1109/CVPR.2008.4587596 IEEE restricted |
| spellingShingle | An, Senjian Liu, Wan-Quan Venkatesh, Svetha Exploiting side information in locality preserving projection |
| title | Exploiting side information in locality preserving projection |
| title_full | Exploiting side information in locality preserving projection |
| title_fullStr | Exploiting side information in locality preserving projection |
| title_full_unstemmed | Exploiting side information in locality preserving projection |
| title_short | Exploiting side information in locality preserving projection |
| title_sort | exploiting side information in locality preserving projection |
| url | http://hdl.handle.net/20.500.11937/30673 |