A regularization method for non-trivial codes in polychotomous classification

International Journal of Pattern Recognition and Artificial Intelligence

Volumn 12, Issue 4, 1998, Pages 453-474

  Utschick, Wolfgang ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Classification; Error correcting output coding; Generalization; Handwritten characters; Neural networks; Optimization; Regularization

Indexed keywords

EID: 0008410199     PISSN: 02180014     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218001498000294     Document Type: Article

References (28)

1. V. Y. Arsenin and A. N. Tikhonov, Solutions of Ill-posed Problems, V. H. Winston, 1977.
2. C. M. Bishop, Neural Networks for Pattern Recognition, Clarendon Press, 1995.
3. L. Breiman, Bagging Predictors, Technical Report 421, Department of Statistics, University of California, Berkely, 1994.
4. H. Bunke and P. S. P. Wang (eds.), Handbook on Optical Character Recognition and Document Analysis, World Scientific Publishing Company, 1996.
5. D. Ciesinger, "Erzeugung von Soll-Ausgangsmustern für Neuronale Netze bei Vielklassenproblemen", Master's Thesis, Technische Universität München, Lehrstuhl für Netzwerktheorie und Schaltungstechnik, 1995.
6. T. G. Dietterich and G. Bakiri, "Solving multiclass learning problems via error correcting output codes", J. Artif. Intell. Res. 2 (1995) 263-286.
7. K. Fukunaga, Introduction to Statistical Pattern Recognition, Academic Press, 1972.
8. J. Gareth and T. Hastie, "Error coding and PaCT's, 1997", Winning paper in the ASA student paper competition for the Statistical Computing Section, see http://playfair.Stanford.EDU/~trevor/ASA/winners.html.
9. D. E. Goldberg, Genetic Algorithms in Search Optimization and Machine Learning, Addison-Wesley, 1989.
10. R. M. Gray, "Vector quantization", Acoustics, Speech, and Signal Processing Magazine 1, 2 (1984) 4-29.
11. R. W. Hamming, Coding and Information Theory, Prentice Hall, 1980.
12. S. Kirkpatrick, C. D. Gelatt and M. V. Vecchi, "Optimization by simulated annealing", Science 220, 4598 (1983) 671-680.
13. E. B. Kong and T. G. Dietterich, "Error-correcting output coding corrects bias and variance", Proc. 12th Int. Conf. Machine Learning, Morgan Kaufmann, Tahoe City, CA, 1995, pp. 313-321.
14. U. Kressel and J. Schürmann, "Pattern classification techniques based on function approximation", Handbook on Optical Character Recognition and Document Analysis, eds. H. Bunke and P. S. P. Wang, Chap. 2, World Scientific Publishing Company, 1996, pp. 49-78.
15. P. Nachbar, "Entwurf robuster neuronaler Netze", PhD Thesis, Technische Universität München, 1994.
16. J. R. Quinlan, "Combining instance-based and model-based learning", Proc. 10th Int. Conf. Machine Learning, Morgan Kaufmann, Amherst, Massachusetts, 1995, pp. 236-243.
17. B. D. Ripley, Pattern Recognition and Neural Networks, Cambridge University Press, 1996.
18. J. Schürmann, Pattern Classification, A Unified View Of Statistical And Neural Approaches, Wiley, 1996.
19. The state-of-the-art in OCR is subject of NIST conference, Intelligence 9, 6 (1992).
20. W. Utschick, P. Nachbar, C. Knobloch, A. Schuler and J. A. Nossek, "The evaluation of feature extraction criteria applied to neural network classifiers", Proc. 3rd Int. Conf. Document Analysis and Recognition, IEEE Computer Society Press, Montreal, 1995, pp. 315-318.
21. W. Utschick and J. A. Nossek, "Bayesian adaptation of hidden layers in Boolean feedforward neural networks", Proc. 13th Int. Conf. Pattern Recognition, IEEE Computer Society Press, Vienna, 1996, pp. 229-233.
22. W. Utschick and J. A. Nossek, "Automatischer Entwurf Paralleler Neuronaler Netze für Mehrklassenprobleme in der Mustererkennung", Mustererkennung 1996, eds. B. Jähne, P. Geißler, H. Haußecker and F. Hering, Informatik Aktuell, Springer, Heidelberg, 1996, pp. 466-474.
23. W. Utschick and J. A. Nossek, "Hybrid optimization of feedforward neural networks for handwritten character recognition", Proc. Int. Conf. Acoustics, Speech, and Signal Processing, IEEE Computer Society Press, Munich, 1997, pp. 147-150.
24. W. Utschick, H.-P. Veit, and J. A. Nossek, "Non-trivial codes for polychotomous classification in pattern recognition", Proc. Int. Conf. Engineering Applications of Neural Networks, Stockholm, 1997, pp. 25-28.
25. V. N. Vapnik, Estimation of Dependences Based on Empirical Data, Springer, 1982.
26. V. N. Vapnik, The Nature of Statistical Learning Theory, Springer, 1995.
27. B. Widrow, "Adaline and madaline", Proc. 1st Int. Conf. on Neural Networks, IEEE Computer Society Press, 1987, pp. 143-158.
28. B. Widrow and M. A. Lehr, "30 years of adaptive neural networks: Perceptron, madaline, and backpropagation", Proc. IEEE 78, 9 (1990) 1415-1441.