Bibliography

1

A.L. Berger, S.A. Della Pietra, and V.J. Della Pietra.
A maximum entropy approach to natural language processing.
Computational Linguistics, 22(1):39-72, March 1996.

2

J. Dahmen, R. Schlüter, and H. Ney.
Discriminative training of Gaussian mixture densities for image object recognition.
In 21. DAGM Symposium Mustererkennung, pages 205-212, Bonn, Germany, September 1999.

3

J.N. Darroch and D. Ratcliff.
Generalized iterative scaling for log-linear models.
Annals of Mathematical Statistics, 43(5):1470-1480, 1972.

4

D. Keysers, F.J. Och, and H. Ney.
Maximum entropy and Gaussian models for image object recognition.
In Pattern Recognition, 24th DAGM Symposium, pages 498-506, Zürich, Switzerland, September 2002.

5

C.J. Merz, P.M. Murphy, and D.W. Aha.
UCI Repository of Machine Learning Databases.
http://www.ics.uci.edu/$\sim$mlearn/MLRepository.html.
University of California, Department of Information and Computer Science, Irvine CA, 1997.

6

D. Michie, D.J. Spiegelhalter, C.C. Taylor (eds).
Machine Learning, Neural and Statistical Classification.
Ellis Horwood, 1994.
Available at http:// www.amsta.leeds.ac.uk/$\sim$charles/statlog/, datasets at http://www.liacc.up.pt/ ML/statlog/datasets.html.

7

K. Nigam, J. Lafferty, and A. McCallum.
Using maximum entropy for text classification.
In IJCAI-99 Workshop on Machine Learning for Information Filtering, pages 61-67, Stockholm, Sweden, August 1999.

8

Y. Normandin.
Maximum mutual information estimation of hidden Markov models.
In C.H. Lee, F.K. Soong, and K.K. Paliwal, editors, Automatic Speech and Speaker Recognition, pages 57-81, Norwell, MA, Kluwer, 1996.

9

R. Paredes and E. Vidal.
A class-dependent weighted dissimilarity measure for nearest-neighbor classification problems.
Pattern Recognition Letters, 21(12):1027-1036, November 2000.