Parameter free large margin nearest neighbor for distance metric learning

31st AAAI Conference on Artificial Intelligence, AAAI 2017

Volumn , Issue , 2017, Pages 2555-2561

  Song, Kun ^a   Nie, Feiping ^a   Han, Junwei ^a   Li, Xuelong ^b  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^b XI AN INSTITUTE OF OPTICS AND PRECISION MECHANICS   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); COST FUNCTIONS; NEAREST NEIGHBOR SEARCH;

CLASSIFICATION RESULTS; DISTANCE METRIC LEARNING; DISTANCE METRICS; GEOMETRY INFORMATION; K-NEAREST NEIGHBORS; LARGE MARGIN NEAREST NEIGHBORS;

LEARNING ALGORITHMS;

EID: 85028561829     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (26)

1. Cheng, G.; Han, J.; Guo, L.; Liu, Z.; Bu, S.; and Ren, J. 2015. Effective and efficient midlevel visual elementsoriented land-use classification using VHR remote sensing images. IEEE Transactions on Geoscience and Remote Sensing 53(8):1-12.
2. Davis, J.; Kulis, B.; and Jain, P. 2007. Information-theoretic metric learning. In Proceedings of the 24th international conference on Machine learning. ACM, 209-216.
3. Do, H.; Kalousis, A.; Wang, J.; and Woznica, A. 2012. A metric learning perspective of svm: on the relation of svm and lmnn. arXiv preprint arXiv:1201.4714.
4. Guillaumin, M., and Verbeek, J. 2009. Is that you? metric learning approaches for face identification. In Computer Vision, 2009 IEEE 12th international conference on, 498-505. IEEE.
5. Han, J.; Zhang, D.; Hu, X.; Guo, L.; Ren, J.; and Wu, F. 2015. Background prior-based salient object detection via deep reconstruction residual. IEEE Transactions on Circuits and Systems for Video Technology 25(8):1309-1321.
6. Han, Q. 1998. Projection and contraction methods for semidefinite programming. Applied Mathematics and Computation 95(2):275-289.
7. Hull, J. J. 1994. A database for handwritten text recognition research. Pattern Analysis and Machine Intelligence, IEEE Transactions on 16(5):550-554.
8. Kedem, D.; Tyree, S.; Sha, F.; Lanckriet, Gert, R.; and Weinberger, Kilian, Q. 2012. Non-linear metric learning. In Advances in Neural Information Processing Systems, 2573-2581.
9. Kedem, D.; Tyree, S. S. F. 2012. Non-linear metric learning. In Advances in Neural Information Processing Systems. 2573-2581.
10. Lu, X., and Wu, H. 2014. Double constrained nmf for hyperspectral unmixing. IEEE Transactions on Geoscience and Remote Sensing 52(5):2746-2758.
11. Lu, X., and Yuan. 2013. Image super-resolution via double sparsity regularized manifold learning. IEEE Transactions on Circuits and Systems for Video Technology 23(12):2022-2033.
12. Ma, L.; Crawford, Melba, M.; and Tian, J. 2010. Local manifold learning based nearest neighbor for hyperspectral image classification. Geoscience and Remote Sensing, IEEE Transactions on 48(11):4099-4109.
13. Mensink, T.; Verbeek, J.; Perronnin, F.; and Csurka, G. 2012. Metric learning for large scale image classification: Generalizing to new classes at near-zero cost. In Computer Vision-ECCV 2012. Springer. 488-501.
14. Nene, Sameer, A.; Nayar, Shree, K.; and Hiroshi, M. 1996. Columbia object image library (coil-20). Technical report, technical report CUCS-005-96.
15. Parameswaran, S., and Weinberger, Kilian, Q. 2010. Large margin multi-task metric learning. In Advances in neural information processing systems, 1867-1875.
16. Perrot, M., and A., H. 2015. Regressive virtual metric learning. In Advances in Neural Information Processing Systems. 1810-1818.
17. Torresani, L., and Lee, K.-C. 2006. Large margin component analysis. In Advances in neural information processing systems, 1385-1392.
18. Vandenberghe, L., and Boyd, S. 1996. Semidefinite programming. SIAM review 38(1):49-95.
19. Wang, H.; Nie, F.; and Huang, H. 2014. Robust distance metric learning via simultaneous l1-norm minimization and maximization. In International Conference on Machine Learning, 1836-1844.
20. Weinberger, Kilian, Q., and Saul, Lawrence, K. 2009. Distance metric learning for large margin nearest neighbor classification. The Journal of Machine Learning Research 10:207-244.
21. Weinberger, Kilian, Q.; Blitzer, J.; and Saul, Lawrence, K. 2005. Distance metric learning for large margin nearest neighbor classification. In Advances in neural information processing systems, 1473-1480.
22. Xiang, S.; Nie, F.; and Zhang, C. 2008. Learning a mahalanobis distance metric for data clustering and classification. Pattern Recognition 41(12):3600-3612.
23. Xing; Eric, P.; Andrew, Y.; Jordan, Michael, I.; and Stuart, R. 2003. Distance metric learning with application to clustering with side-information. Advances in neural information processing systems 15:505-512.
24. Yang, L.; Jin, R., and Sukthankar, R. 2006. An efficient algorithm for local distance metric learning. AAAI 543-548.
25. You, J.; Wu, A.; Li, X.; and Zheng, W.-s. 2016. Top-push video-based person re-identification. 1345-1353.
26. Yuan, S.; Bellet, A.; and Fei, S. 2014. Sparse compositional metric learning. arXiv preprint 1404.4105.