Function dot product Kernels for support vector machine

Proceedings - International Conference on Pattern Recognition

Volumn 2, Issue , 2006, Pages 614-617

  Chen, G Y ^a   Bhattacharya, P ^a  

^a Concordia University ^*  (Canada)

Author keywords

Bhattacharyya kernel; Feature extraction; Function regression; Kernel; Support vector machine

Indexed keywords

FUNCTION EVALUATION; POLYNOMIAL APPROXIMATION; RADIAL BASIS FUNCTION NETWORKS; SUPPORT VECTOR MACHINES; WAVELET TRANSFORMS;

BHATTACHARYYA KERNEL; FUNCTION REGRESSION; SUPPORT VECTOR KERNELS; WAVELET FUNCTION;

FEATURE EXTRACTION;

EID: 34047224357     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2006.586     Document Type: Conference Paper

References (13)

1. Q. Song, W. J. Hu and W. F. Xie, "Robust support vector machine for bullet hole image classification," IEEE Transactions on Systems, Man and Cybernetics - Part C, vol. 32, no. 4, pp. 440-448, 2002.
2. L. Zhang, W. Zhou and L. Jiao, "Wavelet support vector machine," IEEE Transactions on Systems, Man, and Cybernetics - Part B, vol. 34, no. 1, pp. 34-39, 2004.
3. A. Smola, B. Scholkopf and K.-R. Muller, "The connection between regulation operators and support vector kernels," Neural Network, vol. 11, pp. 637-649, 1998.
4. G. Y. Chen and G. Dudek, "Auto-correlation wavelet support vector machine and its applications to regression," Proc. of the 2nd Canadian Conference on Computer and Robot Vision, May 9-11, 2005, British Columbia, Canada.
5. G. Y. Chen and W. F. Xie, "Multiwavelet Support Vector Machines," Proc. of Image and Vision Computing, Dunedin, New Zealand, November 28-29, 2005
6. N. E. Ayat, M. Cheriet and C. Y. Suen, "KMOD - a two-parameter SVM kernel for pattern recognition," Proc. of International Conference on Pattern Recognition, pp. 331-334, 2002.
7. T. Jebara, R. Kondor and A. Howard. "Probability product kernels," Journal of Machine Learning Research, Special Topic on Learning Theory, vol. 5, pp. 819-844, 2004.
8. A. Bhattacharyya, "On a measure of divergence between two statistical populations defined by their probability distribution," Bull. Calcutta Math Soc., 1943.
9. V. N. Vapnik, Statistical learning theory, New York: Wiley, 1998.
10. N. G. Kingsbury, "Complex wavelets for shift invariant analysis and filtering of signals," Journal of Applied and Computational Harmonic Analysis, vol. 10, no. 3, pp. 234-253, 2001.
11. S. Gunn, "Support vector machines for classification and regression," University of Southampton, Southampton, U.K., Image Speech and Intelligent Systems (ISIS) Group, Technical Report, May 1998.
12. T. Joachims, "Estimating the generalization performance of a SVM efficiently," Proc. 17th Int. Conf. Machine Learning, San Fransisco, CA, 2000.
13. M. Kearns and D. Ron, "Algorithmic stability and sanity-check bounds for leave-one-out cross validation," Proc. Tenth Conf. Comput. Learning Theory, New York, pp. 152-162, 1997.