Discriminative canonical correlation analysis with missing samples

2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009

Volumn 6, Issue , 2009, Pages 95-99

  Sun, Tingkai ^a   Chen, Songcan ^b   Yang, Jingyu ^a   Hu, Xuelei ^a   Shi, Pengfei ^c  

^a NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

^c SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CANONICAL CORRELATION ANALYSIS; CLASS INFORMATION; DISCRIMINATIVE FEATURES; FEATURE FUSION; MULTIMODAL RECOGNITION; NOVEL METHODS; REAL APPLICATIONS; RECOGNITION ACCURACY; UNIMODAL;

COMPUTER SCIENCE; FEATURE EXTRACTION;

FACE RECOGNITION;

EID: 70449357004     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CSIE.2009.794     Document Type: Conference Paper

References (13)

1. A. Ross, A. K. Jain. Multimodal biometrics: an overview. In: Proc. of 12th European Signal Processing Conference , Vienna, 2004, pp. 1221-1224.
2. M.Sargin, E. Erzin, Y. Yemez, et al. Multimodal speaker identification using canonical correlation analysis. IEEE International Conference on Acoustics, Speech and Signal Processing, 2006, 1:I-613 - I-616.
3. Hao Pan, Z-P. Liang, Thomas S. Huang. Estimation of the joint probability of multisensory signals. Pattern Recognition Letters, 2001, 22(13):1431-1437.
4. Q. Sun, S. Zeng, et al. A new method of feature fusion and its application in image recognition. Pattern Recognition, 2005, 38(12): 2437-2448.
5. T. Sun, S. Chen, J. Yang, P. Shi, A Novel Method of Combined Feature Extraction for Recognition, IEEE International Conference on Data Mining, pp.1043-1048, Dec.15-19, 2008, Pisa, Italy.
6. B. Walczak, D. Massart. Dealing with missing data Part I. Chemometrics & Intelligent Laboratory Systems, 2001, 58(1):15-27.
7. H. Kim, G. Golub, H. Park. Missing value estimation for DNA microarray gene expression data: local least squares imputation. Bioinformatics, 2005,21:187-198.
8. M. Borga. Canonical correlation: a tutorial. [online] at http://people.imt.liu.se/~magnus/cca/tutorial/, 1999.
9. J. Wegelin. A survey of partial least squares (PLS) methods, with emphasis on the two-block case. Technical Report No.371, Dept. of Statistics, University of Washing, 2000.
10. L. Hoegaerts, J. Suykens, J. Vandewalle, B. De Moor. Subset based least squares subspace regression in RKHS. Neurocomputing, 2005, 63: 293-323.
11. F. Sebastiani. Machine learning in automated text categorization. ACM Computing Surveys, 2002, 34:1-47.
12. J. Rennie. Improving multi-class text classification with naive Bayes. [Master thesis], Massachusetts Institute of Technology, 2001.
13. B. Dasarathy. Nearest neighbor (NN) norms: NN pattern classification techniques. Las Alamitos, California, IEEE Computer Society Press, 1990.