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G. Bebis, Papadourakis, G. M., and Georgiopoulos, M., “Back-Propagation: Increasing rate of convergence by predictable pattern loading”, vol. 1, pp. 14-30, 1989.
J. R. Beck, Garcia, M. E., Zhong, M., Georgiopoulos, M., and Anagnostopoulos, G. C., “A Backward adjusting strategy for the C4.5 decision tree classifier, and the effect of the C4.5 parameters on the tree’s performance”, in 21st Artificial Intelligence Research Symposium, Coconut Grove, FL, 2008.
A. Henninger, Gerber, W., DeMara, R., Georgiopoulos, M., and Gonzalez, A., “Behavior Modeling Framework for Embedded Simulation”, Interservice/Industry Training,Simulation & Education Conference (I/ITSEC 98), pp. 655–662, 1998.
S. J. Verzi, Heileman, G. L., Georgiopoulos, M., and Healy, M. J., “Boosted ARTMAP”, IEEE International Joint Conference on Neural Networks, pp. 396–401, 1998.
S. Verzi, Heileman, G. L., and Georgiopoulos, M., “Boosted ARTMAP: Modifications to fuzzy ARTMAP motivated by boosting Theory”, Neural Networks, vol. 19.4, pp. 446–468, 2006.
G. C. Anagnostopoulos, Georgiopoulos, M., Verzi, S., and Heileman, G., “Boosted ellipsoid ARTMAP”, Proceedings of SPIE,Conference on Applications and Science of Computational Intelligence, vol. 4739, pp. 74–85, 2002.
J. Secretan, Lawson, M., and Boloni, L., “Brokering Algorithms for Composing Low Cost Distributed Storage Resources”, 2007.
A. Koufakou, Wakchaure, A., Kursun, O., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “Burglary data mining – A three tiered approach: Local satte and nation-wide”, in the 2nd Annual GIS Symposium at TU, Troy, Alabama, 2005.
K. Reynolds, Wakchaure, A., Kursun, O., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “Burglary data mining – A three tiered approach: Local state and nation-wide”, in the 2nd Annual GIS Symposium at TU, Troy, Alabama, 2005.