A Faster Iterative Scaling Algorithm For Conditional Exponential Model

Proceedings, Twentieth International Conference on Machine Learning

Volumn 1, Issue , 2003, Pages 282-289

  Jin, Rong ^a   Yan, Rong ^a   Zhang, Jian ^a   Hauptmann, Alex G ^a  

^a Carnegie Mellon University ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CALCULATIONS; DATA ACQUISITION; ERROR CORRECTION; ITERATIVE METHODS; PERSONNEL TRAINING; THEOREM PROVING;

EXPONENTIAL MODEL; ITERATIVE SCALING;

LEARNING SYSTEMS;

EID: 1942484964     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Abramowitz, M. and Stegun, C. A. (Eds.) (1972) Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables, 9th printing. New York: Dover, p. 11, 1972.
2. D. Beeferman, A. Berger and J. Lafferty (1999), Statistical Models for Text Segmentation. In Machine Learning, 34:177-210, 1999.
3. A. Berger, V. Pietra and S. Pietra (1996), A Maximum Entropy Approach to Natural Language Processing. In Computational Linguistics, 22:39-71, 1996.
4. A. Berger (1997), The improved iterative scaling algorithm: A gentle introduction, www.cs.cmu.edu/afs/~aberger/www/ps/scaling.ps
5. A. Borthwick, J. Sterling, E. Agichtein and R. Grishman (1998), Exploiting diverse knowledge sources via maximum entropy in named entity recognition. In Proceedings of the Sixth Workshop on Very Large Corpora, 1998.
6. J. Darroch and D. Ratcli (1972), Generalized iterative scaling for log-linear models. Annals of Math. Statistics, 43(5):1470-1480, 1972.
7. F. Jelinek (1997). Statistical Methods for Speech Recognition. The MIT Press, Cambridge, Massachusetts, London, England, 1997.
8. T. Minka (2001), Algorithms for maximum-likelihood logistic regression, CMU Statistics Tech Report 758, http://www.stat.cmu.edu/~minka/papers/logreg. html, 2001.
9. K. Nigam, J. Lafferty and A. McCallum (1999), Using Maximum Entropy for Text Classification. In IJCAI-99 Workshop on Machine Learning for Information Filtering, 1999.
10. A. Ratnaparkhi (1996), A Maximum Entropy Model for Part-of-Speech Tagging. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, 1996.
11. R. Rosenfeld (1996), A Maximum Entropy Approach to Adaptive Statistical Language Modeling. In Computer, Speech and Language, 10:187-228, 1996.
12. J. Shewchuk (1994), An Introduction to the Conjugate Gradient Method Without the Agonizing Pain, 1994.
13. M. Moller (1993), A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning, Neural Network, 6, 525-533.
14. R. Malouf (2002), A Comparison of Algorithms for Maximum Entropy Parameter Estimation, Proceedings of CoNLL-2002
15. D.C. Liu & J. Nocedal (1989) On the Limited Memory BFGS Method for Large Scale Optimization, Math. Prog. 45, 503-528, 1989