Entropy controlled Laplacian regularization for least square regression

Signal Processing

Volumn 90, Issue 6, 2010, Pages 2043-2049

  Wang, Xinchao ^a   Tao, Dacheng ^b   Li, Zhu ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Face recognition; Least squares; Manifold learning

Indexed keywords

CLASSIFICATION PERFORMANCE; CROSS VALIDATION; DATA SETS; ENTROPY MAXIMIZATION; HUMAN FACES; LABELED AND UNLABELED DATA; LAPLACIANS; LEAST SQUARE; LEAST SQUARE REGRESSION; LINEAR COMBINATION COEFFICIENTS; LINEAR COMBINATIONS; MANIFOLD LEARNING; MATRIX FACTORIZATIONS; NEW MODEL; PATTERN CLASSIFICATION; REGRESSION ERRORS; REGULARIZED LEAST SQUARES; TEST DATA; TRAINING PROCESS; UNLABELED SAMPLES;

CLASSIFICATION (OF INFORMATION); ENTROPY; LAPLACE TRANSFORMS; PROBABILITY DISTRIBUTIONS; REGRESSION ANALYSIS;

FACE RECOGNITION;

EID: 77049107292     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2010.01.006     Document Type: Article

References (21)

1. Belhumeur P., Hespanha J., and Kriegman D. Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans.actions on Pattern Analysis and Machine Intelligence 19 7 (1997) 711-720
2. Belkin M., Niyogi P., and Sindhwani V. Manifold regularization: a geometric framework for learning from Labeled and unlabeled examples. Journal of Machine Learning Research 7 (2006) 2399-2434
3. Cai D., He X., and Han J. SRDA: an efficient algorithm for large scale discriminant analysis. IEEE Transactions on Knowledge and Data Engineering 20 1 (Jan. 2008) 1-12
4. B. Geng, D. Tao, C. Xu, L. Yang, X. Hua, Ensemble Manifold Regularization,manifold regularization, in: IEEE Conference on Computer Vision and Pattern Recognition 2009.
5. He X., Cai D., and Han J. Learning a maximum margin subspace for image retrieval. IEEE Transaction on Knowledge and Date Engineering 20 2 (Feb 2008) 189-201
6. He X., and Niyogi P. Locality preserving projections. Advances in Neural Information Processing Systems 16 (2003)
7. Jadhav D.V., and Holambe R.S. Radon and discrete cosine transforms based feature extraction and dimensionality reduction approach for face recognition. Signal Processing 88 10 (October 2008) 2604-2609
8. Jolliffe I.T. Principal Component Analysis. Second ed.second edition (2002), Springer-Verlag
9. Phillips P.J., Moon H., Rizvi S.A., and Rauss P.J. The FERET evaluation methodology for face-recognition algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 22 10 (2000) 1090-1104
10. Rosenberg S. The Laplacian on a Riemmannian Manifolds (1997), Cambridge University Press
11. Strassen V. Gausssian elimination is not optimal. Numer. Math.ische Mathematik 13 (1969)
12. Xiao B., Gao X., Tao D., and Li X. A new approach for face recognition by sketches in photos. Signal Processing 89 8 (August 2009) 1576-1588
13. J. Ye, Least Squares Linear Discriminant Analysis,squares linear discriminant analysis, in: The Twenty-Fourth24th International Conference on Machine Learning, 2007.
14. W. Zuo, H. Zhang, D. Zhang, K. Wang, Post-processed LDA for face and palmprint recognition: Whatwhat is the rationale, Signal Processing 2009.
15. D. Cai, X. He, Orthogonal Locality Preserving Indexing., in: The 28th Annual International ACM SIGIR Conference 2005.
16. Zhang T., Tao D., Li X., and Yang J. Patch alignment for dimensionality reduction. IEEE Transactions on Knowledge and Data Engineering 21 9 (2009) 1299-1313
17. Tao D., Li X., Wu X., and Maybank S.J. Geometric mean for subspace selection. IEEE Transactions on Pattern Analysis and Machine Intelligence 31 2 (2009) 260-274
18. W. Liu, D. Tao, J. Liu, Transductive component analysis, in: IEEE International Conference on Data Mining, 2008, pp. 433-442.
19. Tao D., Li X., Wu X., and Maybank S.J. General tensor discriminant analysis and gabor features for gait recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 29 10 (2007) 1700-1715
20. W. Bian, D. Tao, Harmonic mean for subspace selection, in: IEEE International Conference on Pattern Recognition, 2008, pp. 1-4.
21. Tao D., Li X., Wu X., Hu W., and Maybank S.J. Supervised tensor learning. Knowledge and Information Systems 13 1 (2007) 1-42