A scalable dual approach to semidefinite metric learning

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2011, Pages 2601-2608

  Shen, Chunhua ^a,b   Kim, Junae ^b,c   Wang, Lei ^c,d  

^a UNIVERSITY OF ADELAIDE   (Australia)

^b CSIRO   (Australia)

^c AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

^d UNIVERSITY OF WOLLONGONG   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

PATTERN RECOGNITION;

DISTANCE METRIC LEARNING; HIGH-DIMENSIONAL PROBLEMS; MAHALANOBIS METRIC; MAXIMUM VARIANCE; SEMI-DEFINITE PROGRAMMING; STATE OF THE ART; TIME COMPLEXITY; VISION PROBLEMS;

PROBLEM SOLVING;

EID: 80052905593     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2011.5995447     Document Type: Conference Paper

References (24)

1. B. Borchers. CSDP, a C library for semidefinite programming. Optim. Methods and Softw., 11(1):613-623, 1999.
2. J. Borwein and A. Lewis. Convex Analysis and Nonlinear Optimization. Springer-Verlag, New York, 2000.
3. S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, 2004.
4. Z. Cao, Q. Yin, X. Tang, and J. Sun. Face recognition with learning-based descriptor. In Proc. IEEE Conf. Comp. Vis. Pattern Recogn., 2010.
5. J. V. Davis, B. Kulis, P. Jain, S. Sra, and I. S. Dhillon. Information-theoretic metric learning. In Proc. Int. Conf. Mach. Learn., pages 209-216, Corvalis, Oregon, 2007. ACM Press.
6. J. Goldberger, S. Roweis, G. Hinton, and R. Salakhutdinov. Neighbourhood component analysis. In Proc. Adv. Neural Inf. Process. Syst. MIT Press, 2004.
7. M. Guillaumin, J. Verbeek, and C. Schmid. Is that you? metric learning approaches for face identification. In Proc. IEEE Int. Conf. Comp. Vis., 2009.
8. G. B. Huang, M. J. Jones, and E. Learned-Miller. LFW results using a combined nowak plus merl recognizer. In Faces in Real-Life Images Workshop, in Euro.
9. G. B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller. Labeled faces in the wild: A database for studying face recognition in unconstrained environments. Technical Report 07-49, University of Massachusetts, Amherst, October 2007.
10. N. Kumar, A. C. Berg, P. N. Belhumeur, and S. K. Nayar. Attribute and simile classifiers for face verification. In Proc. IEEE Int. Conf. Comp. Vis., 2009.
11. D. C. Liu and J. Nocedal. On the limited memory BFGS method for large scale optimization. Math. Program.: Series A and B, 45(3):503-528, 1989.
12. D. G. Lowe. Distinctive image features from scale-invariant keypoints. Int. J. Comp. Vis., 60(2):91-110, 2004.
13. E. Nowak and F. Jurie. Learning visual similarity measures for comparing never seen objects. In Proc. IEEE Conf. Comp. Vis. Pattern Recogn., 2007.
14. N. Pinto, J. DiCarlo, and D. Cox. How far can you get with a modern face recognition test set using only simple features? In Proc. IEEE Conf. Comp. Vis. Pattern Recogn., 2009.
15. G. Raetsch, B. Schoelkopf, A. Smola, K. R. Muller, T. Onoda, and S. Mika. ν-Arc: Ensemble learning in the presence of outliers. In Proc. Adv. Neural Inf. Process. Syst., pages 561-567. MIT Press, 2000.
16. C. Shen, J. Kim, L. Wang, and A. van den Hengel. Positive semidefinite metric learning with boosting. In Proc. Adv. Neural Inf. Process. Syst., pages 1651-1659, 2009.
17. N. Shental, T. Hertz, D. Weinshall, and M. Pavel. Adjustment learning and relevant component analysis. In Proc. Euro. Conf. Comp. Vis., volume 4, pages 776-792, London, UK, 2002. Springer-Verlag.
18. Y. Taigman, L. Wolf, and T. Hassner. Multiple one-shots for utilizing class label information. In Proc. British Mach. Vis. Conf, 2009.
19. M. A. Turk and A. P. Pentland. Face recognition using eigenfaces. In Proc. IEEE Conf. Comp. Vis. Pattern Recogn., 1991.
20. K. Q. Weinberger, J. Blitzer, and L. K. Saul. Distance metric learning for large margin nearest neighbor classification. J. Mach. Learn. Res., 10:207-244, 2009.
21. K. Q. Weinberger and L. K. Saul. Unsupervised learning of image manifolds by semidefinite programming. Int. J. Comp. Vis., 70(1):77-90, 2005.
22. L. Wolf, T. Hassner, and Y. Taigman. Descriptor based methods in the wild. In Faces in Real-Life Images Workshop, in Euro. Conf. Comp. Vision, 2008.
23. L. Wolf, T. Hassner, and Y. Taigman. Similarity scores based on background samples. In Proc. Asian Conf. Comp. Vis., 2009.
24. E. Xing, A. Ng, M. Jordan, and S. Russell. Distance metric learning, with application to clustering with side-information. In Proc. Adv. Neural Inf. Process. Syst. MIT Press, 2002.