Semisupervised dimensionality reduction and classification through virtual label regression

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 41, Issue 3, 2011, Pages 675-685

  Nie, Feiping ^a   Xu, Dong ^a   Li, Xuelong ^b   Xiang, Shiming ^c  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

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

^c INSTITUTE OF AUTOMATION   (China)

Author keywords

Dimensionality reduction; label propagation; label regression; semisupervised learning; subspace learning

Indexed keywords

DIMENSIONALITY REDUCTION; LABEL INFORMATION; LABEL PROPAGATION; LABELED AND UNLABELED DATA; LABELED DATA; LINEAR MODEL; PROJECTION MATRIX; RANDOM WALK; SEMI-SUPERVISED; SEMI-SUPERVISED LEARNING; SUBSPACE LEARNING; UNLABELED DATA; VIRTUAL LABELS; WEIGHTED REGRESSION;

REGRESSION ANALYSIS;

DATA REDUCTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER SIMULATION; DECISION SUPPORT SYSTEM; METHODOLOGY; THEORETICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DECISION SUPPORT TECHNIQUES; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED;

EID: 79957454703     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2010.2085433     Document Type: Article

References (39)

1. Y. Pang, Y. Yuan, and X. Li, "Gabor-based region covariance matrices for face recognition," IEEE Trans. Circuits Syst. Video Technol., vol. 18, no. 7, pp. 989-993, Jul. 2008.
2. D. Dai and P. C. Yuen, "Face recognition by regularized discriminant analysis," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 37, no. 4, pp. 1080-1085, Aug. 2007. (Pubitemid 47103958)
3. X. Li, S. Lin, S. Yan, and D. Xu, "Discriminant locally linear embedding with high-order tensor data," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 38, no. 2, pp. 342-352, Apr. 2008. (Pubitemid 351479557)
4. Y. Pang, Y. Yuan, and X. Li, "Effective feature extraction in high dimensional space," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 38, no. 6, pp. 1652-1656, Dec. 2008.
5. Y. Yang, F. Wu, D. Xu, Y. Zhuang, and L.-T. Chia, "Cross-media retrieval using query dependent search methods," Pattern Recognit., vol. 43, no. 8, pp. 2927-2936, Aug. 2010.
6. R. Dudoit, J. Fridly, and T. P. Speed, "Comparison of discrimination methods for the classification of tumors using gene expression data," J. Amer. Stat. Assoc., vol. 97, no. 457, pp. 77-87, Mar. 2002.
7. S. Xiang, F. Nie, C. Zhang, and C. Zhang, "Interactive natural image segmentation via spline regression," IEEE Trans. Image Process., vol. 18, no. 7, pp. 1623-1632, Jul. 2009.
8. Y. Pang, D. Tao, Y. Yuan, and X. Li, "Binary two-dimensional PCA," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 38, no. 4, pp. 1176-1180, Aug. 2008.
9. Y. Pang, Y. Yuan, and X. Li, "Iterative subspace analysis based on feature line distance," IEEE Trans. Image Process., vol. 18, no. 4, pp. 903-907, Apr. 2009.
10. Y. Yuan, X. Li, Y. Pang, X. Lu, and D. Tao, "Binary sparse nonnegative matrix factorization," IEEE Trans. Circuits Syst. Video Technol., vol. 19, no. 5, pp. 772-777, May 2009.
11. X. Li and Y. Pang, "Deterministic column-based matrix decomposition," IEEE Trans. Knowl. Data Eng., vol. 22, no. 1, pp. 145-149, Jan. 2010.
12. X. Li, Y. Pang, and Y. Yuan, "L1-norm-based 2DPCA," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 40, no. 4, pp. 1170-1175, Aug. 2010, DOI: 10.1109/TSMCB.2009.2035629.
13. K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. Boston, MA: Academic, 1990.
14. X. J. Zhu, "Semi-supervised learning literature survey," Dept. Comput. Sci., Univ. Wisconsin-Madison, Madison, Tech. Rep. 1530, 2007.
15. X. Zhu, Z. Ghahramani, and J. D. Lafferty, "Semi-supervised learning using Gaussian fields and harmonic functions," in Proc. ICML, 2003, pp. 912-919.
16. D. Zhou, O. Bousquet, T. N. Lal, J. Weston, and B. Schölkopf, "Learning with local and global consistency," in Proc. NIPS, 2004, pp. 321-328.
17. Y. Bengio, J.-F. Paiement, P. Vincent, O. Delalleau, N. L. Roux, and M. Ouimet, "Out-of-sample extensions for LLE, ISOMAP, MDS, eigenmaps, and spectral clustering," in Proc. NIPS, 2003, pp. 177-184.
18. D. Zhang, Z.-H. Zhou, and S. Chen, "Semi-supervised dimensionality reduction," in Proc. SDM, 2007, pp. 629-634.
19. D. Cai, X. He, and J. Han, "Semi-supervised discriminant analysis," in Proc. ICCV, 2007, pp. 1-7.
20. Y. Song, F. Nie, C. Zhang, and S. Xiang, "A unified framework for semisupervised dimensionality reduction," Pattern Recognit., vol. 41, no. 9, pp. 2789-2799, Sep. 2008.
21. M. Sugiyama, T. Idé, S. Nakajima, and J. Sese, "Semi-supervised local fisher discriminant analysis for dimensionality reduction," in Proc. PAKDD, 2008, pp. 333-344. (Pubitemid 351776328)
22. Y. Song, F. Nie, and C. Zhang, "Semi-supervised sub-manifold discriminant analysis," Pattern Recognit. Lett., vol. 29, no. 13, pp. 1806-1813, Oct. 2008.
23. F. Wu, W. Wang, Y. Yang, Y. Zhuang, and F. Nie, "Classification by semi-supervised discriminative regularization," Neurocomputing, vol. 73, no. 10-12, pp. 1641-1651, Jun. 2010.
24. C. Hou, C. Zhang, Y. Wu, and F. Nie, "Multiple view semi-supervised dimensionality reduction," Pattern Recognit., vol. 43, no. 3, pp. 720-730, Mar. 2010.
25. M. Belkin, P. Niyogi, and V. Sindhwani, "Manifold regularization: A geometric framework for learning from labeled and unlabeled examples," J. Mach. Learn. Res., vol. 7, pp. 2399-2434, Dec. 2006. (Pubitemid 44708005)
26. S. Yan, D. Xu, B. Zhang, H. Zhang, Q. Yang, and S. Lin, "Graph embedding and extensions: A general framework for dimensionality reduction," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 1, pp. 40-51, Jan. 2007. (Pubitemid 46415944)
27. S. T. Roweis and E. Al, "Nonlinear dimensionality reduction by locally linear embedding," Science, vol. 290, no. 5500, pp. 2323-2326, Dec. 2000. (Pubitemid 32041578)
28. Z. Zhang and H. Zha, "Principal manifolds and nonlinear dimension reduction via local tangent space alignment," SIAM J. Sci. Comput., vol. 26, no. 1, pp. 313-338, 2005. (Pubitemid 40297703)
29. S. Xiang, F. Nie, C. Zhang, and C. Zhang, "Nonlinear dimensionality reduction with local spline embedding," IEEE Trans. Knowl. Data Eng., vol. 21, no. 9, pp. 1285-1298, Sep. 2009.
30. C. Zhang, F. Nie, and S. Xiang, "A general kernelization framework for learning algorithms based on kernel PCA," Neurocomputing, vol. 73, no. 4-6, pp. 959-967, Jan. 2010.
31. C. C. Paige and M. A. Saunders, "Algorithm 583, LSQR: Sparse linear equations and least-squares problems," ACM Trans. Math. Softw., vol. 8, no. 2, pp. 195-209, Jun. 1982.
32. D. Cai, "Spectral regression: A regression framework for efficient regularized subspace learning," Ph.D. dissertation, Dept. Comput. Sci., Univ. Illinois Urbana-Champaign, Urbana, May, 2009.
33. J. H. Friedman, "Regularized discriminant analysis," J. Amer. Stat. Assoc., vol. 84, no. 405, pp. 165-175, Mar. 1989.
34. V. Sindhwani, P. Niyogi, M. Belkin, and S. Keerthi, "Linear manifold regularization for large scale semi-supervised learning," in Proc. ICML Workshop, 2005, pp. 80-83.
35. D. B. Graham and N.M. Allinson, "Characterizing virtual eigensignatures for general purpose face recognition," in Face Recognition: From Theory to Applications, vol. 163, NATO ASI Series F, Computer and Systems Sciences. Berlin, Germany: Springer-Verlag, 1998, pp. 446-456.
36. S. A. Nene, S. K. Nayar, and H. Murase, "Columbia object image library (COIL-20)," Columbia Univ., New York, Tech. Rep. CUCS-005-96, 1996.
37. A. Georghiades, P. Belhumeur, and D. Kriegman, "From few to many: Illumination cone models for face recognition under variable lighting and pose," IEEE Trans. Pattern Anal. Mach. Intell., vol. 23, no. 6, pp. 643-660, Jun. 2001. (Pubitemid 32585276)
38. T. Sim and S. Baker, "The CMU pose, illumination, and expression database," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 12, pp. 1615-1618, Dec. 2003.
39. A. N. Tikhonov and V. Y. Arsenin, Solutions of Ill-Posed Problems. New York: Wiley, 1977.