Large margin nearest local mean classifier

Signal Processing

Volumn 90, Issue 1, 2010, Pages 236-248

  Chai, Jing ^a   Liu, Hongwei ^a   Chen, Bo ^b   Bao, Zheng ^a  

^a XIDIAN UNIVERSITY   (China)

^b Duke University   (United States)

Author keywords

Dimension; Eigenvalue decomposition; Large margin; Linear transformation; Local mean vector; Semidefinite programming

Indexed keywords

DIMENSION; EIGENVALUE DECOMPOSITION; LARGE MARGIN; LINEAR TRANSFORMATION; LOCAL MEAN VECTOR; SEMIDEFINITE PROGRAMMING;

CLASSIFIERS; LEARNING SYSTEMS; MACHINE DESIGN;

EIGENVALUES AND EIGENFUNCTIONS;

EID: 69249222519     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2009.06.015     Document Type: Article

References (27)

1. L. Yang, An overview of distance metric learning, Technical Report, School of Computer Science, Carnegie Mellon University, 2007.
2. Cristianini N., and Shawe-Taylor J. An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods (2000), Cambridge University Press, Cambridge
3. Burges C.J.C. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery 2 2 (1998) 121-167
4. Duda R.O., Hart P.E., and Stork D.G. Pattern Classification (2001), Wiley, New York
5. E. Xing, A. Ng, M. Jordan, S. Russell, Distance metric learning, with application to clustering with side information, in: Proceedings of the NIPS, 2002.
6. R. Gilad-Bachrach, A. Navot, N. Tishby, Margin based feature selection-theory and algorithms, in: Proceedings of the ICML, 2004.
7. K.Q. Weinberger, J. Blitzer, L.K. Saul, Distance metric learning for large margin nearest neighbor classification, in: Proceedings of the NIPS, 2006.
8. J. Goldberger, S. Roweis, G. Hinton, R. Salakhutdinov, Neighbourhood components analysis, in: Proceedings of the NIPS, 2005.
9. A. Globerson, S. Roweis, Metric learning by collapsing classes, in: Proceedings of the NIPS, 2006.
10. L. Torresani, K. Lee, Large margin component analysis, in: Proceedings of the NIPS, 2006.
11. Veenman C.J., and Tax D.M.J. LESS: a model-based classifier for sparse subspaces. IEEE Trans. Pattern Anal. Mach. Intell. 27 9 (2005) 1496-1500
12. Jenssen R., Erdogmus D., Principe J.C., and Eltoft T. The Laplacian classifier. IEEE Trans. Signal Process. 55 7 (2007) 3262-3271
13. Peltonen J., and Kaski S. Discriminative components of data. IEEE Trans. Neural Networks 16 1 (2005) 68-83
14. Fisher R.A. The use of multiple measures in taxonomic problems. Ann. Eugenics 7 (1936) 179-188
15. Belhumeur P.N., Hespanha J.P., and Kriengman D.J. Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 19 7 (1997) 711-720
16. L. Yang, R. Jin, R. Sukthankar, Y. Liu, An efficient algorithm for local distance metric learning, in: Proceedings of the AAAI, 2006.
17. A. Ng, M. Jordan, Y. Weiss, On spectral clustering: analysis and an algorithm, in: Proceedings of the NIPS, 2001.
18. Vandenberghe L., and Boyd S. Semidefinite programming. SIAM Rev. 38 1 (1996) 49-95
19. Boyd S., and Vandenberghe L. Convex Optimization (2004), Cambridge University Press, Cambridge, UK
20. Golub G.H., and Loan C.F.V. Matrix Computations. third ed. (1996), The John Hopkins University Press, Baltimore, Maryland
21. C. Blake, E. Keogh, C.J. Merz, UCI Repository of Machine Learning Databases, Department of Information Computer Science, University California, Irvine, CA, 1998, Available from: 〈http://www.ics.uci.edu/mlearn〉.
22. Gianfelici F., Turchetti C., and Crippa P. A non-probabilistic recognizer of stochastic signals based on KLT. Signal Process. 89 4 (2009) 422-437
23. M. Grant, S. Boyd, Y. Ye, CVX toolbox, Available from: 〈http://www.stanford.edu/~boyd/cvx〉.
24. Pei B., and Bao Z. Bispectrum based approach to high radar range profile for automatic target recognition. Pattern Recognition 35 11 (2002) 2643-2651
25. Du L., Liu H., Bao Z., and Xing M. Radar HRRP target recognition based on higher order spectra. IEEE Trans. Signal Process. 53 7 (2005) 2359-2368
26. Du L., Liu H., Bao Z., and Zhang J. A two-distribution compounded statistical model for radar HRRP target recognition. IEEE Trans. Signal Process. 54 6 (2006) 2226-2238
27. Xing M., Bao Z., and Pei B. Properties of high-resolution rang profiles. Opt. Eng. 41 2 (2002) 493-504