Dragos D. Margineantu
Publications
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Dragos Margineantu (2002):
Class Probability Estimation and Cost-Sensitive Classification Decisions -
Machine Learning: ECML 2002, Proceedings of the 13th European Conference on Machine Learning, pp.270-281, ©Springer Verlag, Lecture Notes in Artificial Intelligence, 2430.
Postscript preprint. -
Dragos Margineantu, Thomas G. Dietterich (2002):
Improved Class Probability Estimates from Decision Tree Models -
"Nonlinear Estimation and Classification", C.Holmes ed., ©Springer Verlag, Lecture Notes in Statistics.
Postscript preprint -
Dragos Margineantu, Thomas G. Dietterich (2001):
Lazy Class Probability Estimators -
Proceedings of the 33rd Symposium on the Interface of Computing Science and Statistics, Costa Mesa, CA.
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Dragos Margineantu, Thomas G. Dietterich (2000):
Bootstrap Methods for the Cost-Sensitive Evaluation of Classifiers -
Proceedings of the Seventeenth International Conference on Machine Learning (ICML-2000), pp.583-590, Morgan Kaufmann, San Francisco, CA.
Postscript preprint. -
Dragos Margineantu (1999):
Building Ensembles of Classifiers for Loss Minimization -
Proceedings of the 31st Symposium on the Interface: Models, Prediction, and Computing, pp.190-194.
Postscript preprint -
Dragos Margineantu (1999):
Applying Supervised Learning to Real-World Problems -
Proceedings of the Sixteenth National Confernce on Artificial Intelligence (AAAI-99), pp.951. Presented at the SIGART/AAAI-99 Doctoral Consortium.
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Dragos Margineantu, Thomas G. Dietterich (1997):
Pruning Adaptive Boosting -
Proceedings of the Fourteenth International Conference on Machine Learning (ICML-97), pp.211-218, Morgan Kaufmann, San Francisco, CA.
Postscript preprint -
Daniela Crivianu-Gaita, Florin Miclea,
Andrei Gaspar, Dragos Margineantu, and Stefan Holban (1997):
3D reconstruction of prostate from ultrasound images -
International Journal of Medical Informatics, Vol.45, June 1997, pp.43-51, Elsevier Science.
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Dragos Margineantu (1997):
Learning by using dynamic feature combination and selection -
Proceedings of the IASTED/AAAI International Conference on Artificial Intelligence and Soft Computing, pp.154-156, ACTA-IASTED Press, Anaheim, CA.
Postscript preprint. -
Stephane Chatre, Charles Knutson,
Dragos Margineantu, Carsten Schulz-Key (1996):
Improving the DLX Performance by Taking Some of the Reduction out of RISC -
Proceedings of the International Conference on Technical Informatics (ConTI-96), Timisoara, Romania.
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Florin Miclea, Stefan Holban, Andrei Gaspar, Daniela Crivianu-Gaita, Dragos Margineantu (1995):
Modeling and Volume Determination of the Prostate -
Proceedings of the Symposium on Automatic Control and Computer Science (SACCS-95), Iasi, Romania.
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Dragos Margineantu (2001):
Methods for Cost-Sensitive Learning -
Oregon State University, Department of Computer Science (Technical Report)
Postscript preprint -
Dragos Margineantu (2000):
On Class Probability Estimates and Cost-Sensitive Evaluation of Classifiers -
Workshop on Cost-Sensitive Learning, The Seventeenth International Conference on Machine Learning (ICML-2000).
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Dragos Margineantu (2000):
When Does Imbalanced Data Require more than Cost-Sensitive Learning? -
Workshop on Learning from Imbalanced Data, National Conference on Artificial Intelligence (AAAI-2000)
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Dragos Margineantu, Thomas G. Dietterich (1999):
Learning Decision Trees for Loss Minimization in Multi-Class Problems -
Technical Report 99-30-03, Department of Computer Science, Oregon State University
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Dragos Margineantu, Julianne Monell (1996):
The equivalence of Post systems and Turing machines -
Technical Report, Oregon State University
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Dragos Margineantu (2001):
Learning Ensembles for Probability Estimation and Ranking -
Annual Conference of the Institute for Operations Research and Management Sciences (INFORMS), November 2001
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Dragos Margineantu (1998):
Issues in Applying Divide-and-Conquer Methods for Learning Real-World Problems -
Neural Information Processing Systems 1998 (NIPS-98), workshop on "Learning from Ambiguous and Complex Examples"