Classification in likelihood spaces

Technometrics

Volumn 46, Issue 3, 2004, Pages 318-329

  Singh, Rita ^a   Raj, Bhiksha ^b  

^a Carnegie Mellon University   (United States)

^b MITSUBISHI ELECTRIC RESEARCH LABORATORIES   (United States)

Author keywords

Discriminant based classifiers; Distribution based classifiers; Likelihood projections

Indexed keywords

DISCRIMINANT-BASED CLASSIFIERS; DISTRIBUTION-BASED CLASSIFIERS; LIKELIHOOD PROJECTIONS;

APPROXIMATION THEORY; CLASSIFICATION (OF INFORMATION); COMPUTATIONAL METHODS; DATA ACQUISITION; ERROR CORRECTION; FUNCTIONS; MATHEMATICAL MODELS; PATTERN RECOGNITION; PROBABILITY DISTRIBUTIONS;

DISTRIBUTED DATABASE SYSTEMS;

EID: 4544238898     PISSN: 00401706     EISSN: None     Source Type: Trade Journal    
DOI: 10.1198/004017004000000347     Document Type: Article

References (37)

1. Brand, M. (2002), "Charting a Manifold," Proceedings on Neural Information Processing Systems, Vancouver, BC, Canada.
2. Breiman, L., Friedman, J. H., Olshen, R. A., and Stone, C. J. (1984), Classification and Regression Trees, Belmont, CA: Wadsworth.
3. Brodatz, P. (1966), Textures: A Photographic Album for Artists and Designers, New York: Dover.
4. Brown, H., and Prescott, R. (2000), Applied Mixed Models in Medicine, London: Wiley.
5. Burges, C. J. C. (1998), "A Tutorial on Support Vector Machines for Pattern Recognition," Data Mining and Knowledge Discovery, 2, 1-43.
6. Conlon, L. (1993), Differentiate Manifolds: A First Course, Cambridge, MA: Birkhäuser.
7. Cortes, C., and Vapnik, V. (1995), "Support Vector Networks," Machine Learning. 20, 273-297.
8. Darlington, R. B. (1990), Regression and Linear Models, New York: McGraw-Hill.
9. Davis, S. B., and Mermelstein, P. (1980), "Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Sentences," IEEE Transactions on Acoustics, Speech, and Signal Processing, 28, 357-366.
10. Dawid, A. P. (1976), "Properties of Diagnostic Data Distributions," Biometrics, 32, 647-658.
11. Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977), "Maximum Likelihood From Incomplete Data via the EM Algorithm" (with discussion), Journal of the Royal Statistical Society, Ser. B, 39, 1-38.
12. Dietterich, T., and Bakiri, G. (1995), "Solving Multiclass Learning Problems via Error-Correcting Output Codes," Journal of Artificial Intelligence Research, 2, 263-286.
13. Duda, R. O., Hart, P. E., and Stork, D. G. (2000), Pattern Classification (2nd ed.), New York: Wiley.
14. Durbin, R., Eddy, S., Krogh, A., and Mitchison, G. (1999), Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, Cambridge, U.K.: Cambridge University Press.
15. Friedman, J. H. (1996), "Another Approach to Polychotomous Classification," technical report, Stanford University, Dept. of Statistics.
16. Gupta P. L., Riley J. T., and White T. J. (1986), "Misclassification Probabilities for Quadratic Discrimination," SIAM Journal of Scientific and Statistical Computing, 7, 1400-1417.
17. Hastie, T., and Tibshirani, R. (1998), "Classification by Pairwise Coupling," The Annals of Statistics, 26, 451-471.
18. Hermansky, H., Ellis, D. P. W., and Sharma, S (2000), "Tandem Connectionist Feature Extraction for Conventional HMM Systems." in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP2000, Istanbul, Turkey, pp. 1635-1638.
19. Highleyman, W. H. (1962), "Linear Decision Functions With Applications to Pattern Recognition." Proceeding of the IRE, 50, 1501-1514.
20. Huang, X. D., Acero, A., and Hon, H. (2001), Spoken Language Processing, Englewood Cliffs, NJ: Prentice-Hall.
21. Jain, A. K. (1976), "A Fast Karhuncn-Loeve Transform for a Class of Random Processes," IEEE Transactions on Communications, 24, 1023-1029.
22. Lee, Y., Lin, Y., and Wahba, G. (2001), "Multicategory Support Vector Machines," Technical Report TR-1043, University of Wisconsin, Dept. of Statistics.
23. Mantengna, R. N., and Stanley, H. E, (2000), An Introduction to Econophysics: Correlations and Complexity in Finance, Cambridge. U.K.: Cambridge University Press.
24. McLachlan, G. J. (1992), Discriminant Analysis and Statistical Pattern Recognition. New York: Wiley.
25. McLachlan, C. J., and Peel, D. (2000), Finite Mixture Models, New York: Wiley.
26. Normandin, Y., Cardin, R. and De Mori, R. (1994), "High-Performance Connected Digit Recognition Using Maximum Mutual Information Estimation," IEEE Transactions on Speech and Audio Processing, 26, 299-311.
27. Parzen, E. (1962), "On the Estimation of a Probability Density Function and Mode," Annals of Mathematical Statistics, 33, 1065-1076
28. Picard, R. W., Kabir, T., and Liu, F. (1993), "Real-Time Recognition With the Entire Brodatz Texture Database," Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, New York, NY, pp. 638-639.
29. Schölkopf, B., Mika, S., Burges, C., Knirsch, P., Müller, L.-R., Ratsch, G., and Smola, A. J. (1999), "Input Space vs. Feature Space in Kernel-Based Methods," IEEE Transactions on Neural Networks, 10, 1000-1017.
30. Schölkopf, B., Sung, K. K., Burges, C. C., Girosi, F., Niyogi. P., Poggio, T., and Vapnik, V. (1997), "Comparing Support Vector Machines With Gaussian Kernels to Radial Basis Function Classifiers," IEEE Transactions On Signal Processing, 45, 2758-2765.
31. Siegel, S. (1956), Nonparametric Statistics for the Behavioral Sciences, New York: McGraw-Hill.
32. Tresp, V. (2001), "Mixtures of Gaussian Processes," in Advances in Neural Information and Processsing Systems 13, eds. T. K. Leen, T. G Dietteriech, and V. Tresp, Cambridge, MA: MIT Press.
33. Vapnik, V. (1998), Statistical Learning Theory, New York: Wiley.
34. Vasconcelos, N., and Carneiro, G. (2002), "What Is the Role of Independence for Visual Recognition?" in Proceedings of the European Conference on Computer Vision, Copenhagen, Denmark.
35. Weston, J., and Watkins, K. (1998), "Multiclass Support Vector Machines," Technical Report CSD-TR-98-04, University of London.
36. Wilks, D. S. (1995), Statistical Methods in the Atmospheric Sciences: An Introduction, London: Academic Press.
37. Zue, V., Seneff, S., and Glass, J. (1990), "Speech Database Development at MIT: TIMIT and Beyond," Speech Communication. 9, 351-356.