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A
A. Al-Dairaiseh, Kaylani, A., Georgiopoulos, M., Mollaghasemi, M., Wu, A. S., and Anagnostopoulos, G., “GFAM Evolving Fuzzy ARTMAP Neural Networks”, Neural Networks journal, vol. 20, pp. 874-892, 2007.
A. Al-Dairaseh, Georgiopoulos, M., Wu, A. S., Anagnostopoulos, G., and Mollaghasemi, M., “GFAM: A genetic algorithm optimization of Fuzzy ARTMAP”, in WCCI 2006 (Fuzzy Systems), Vancouver, Canada, 2006.
A. Al-Daraiseh, Kaylani, A., Georgiopoulos, M., Mollaghasemi, M., Anagnostopoulos, G. C., and Kaburlasos, V. G., “Genetically Engineered ART Architectures”, Heidelberg: Springer-Verlag,in Computational Intelligence Based on Lattice Theory,Studies in Computational Intelligence, vol. 67, pp. 233–262, 2007.
A. Al-Daraiseh, Kaylani, A., Georgiopoulos, M., Wu, A. S., Mollaghasemi, M., and Anagnostopoulos, G. C., “GFAM:Evolving Fuzzy ARTMAP Neural Networks”, vol. 20.8, pp. 874–892, 2007.
B
G. Bebis, Uthiram, S., and Georgiopoulos, M., “Genetic Search for Face Detection and Verification”, IEEE International Conference on Information,Intelligence and Systems, pp. 360–367, 1999.
G
M. Georgiopoulos, Dagher, I., Heileman, G. L., and Bebis, G., “The generalization capabilities of ARTMAP”, in International Conference on Neural Networks, Houston, TX, 1997.
H
G. L. Heileman, Georgiopoulos, M., and Roome, W. D., “A general framework for concurrent simulation on neural network models”, in International Joint Conference on Neural Networks (IJCNN), Baltimore, MD, 1992.
G. L. Heileman, Georgiopoulos, M., and Roome, W. D., “A general framework for concurrent simulation on neural network models”, IEEE Transactions on Software Engineering, vol. 18, pp. 551-562, 1992.
K
A. Kaylani, Al-Daraiseh, A., Georgiopoulos, M., Mollaghasemi, M., Anagnostopoulos, G. C., and Wu, A. S., “Genetic Optimization of ART Neural Network Architectures”, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2007), pp. 379–384, 2007.
M
R. Miguez, Georgiopoulos, M., and Kaylani, A., “A Genetically Engineered Probabilistic Neural Network”, Nonlinear Analysis: Theory, Methods & Applications, vol. 73, pp. 1783-1791, 2010.
R
J. Reeder and Georgiopoulos, M., “Generative Neural Networks for Multi-Task Life-Long Learning”, The Computer Journal, vol. 57, no. 3, pp. 427-450, 2014.
Z
M. Zhong, Georgiopoulos, M., Anagnostopoulos, G. C., and Mollaghasemi, M., “Generalized Entropy for Splitting Numerical Attributes in Decision Tree Classifiers”, Proceedings of the 19th International Florida Artificial Intelligence Research Society (FLAIRS) Conference (FLAIRS 2006), pp. 604–609, 2006.
M. Zhong, Coggeshall, D., Ghaneie, E. G., Pope, T., Rivera, M. A., Georgiopoulos, M., and Anagnostopoulos, G. C., “Gap-Based Estimation: Choosing the smoothing parameters for Probabilistic and General Regression Neural Networks”, in WCCI 2006, Vancouver, Canada, 2006.
M. Zhong, Coggeshall, D., Georgiopoulos, M., Anagnostopoulos, G. C., Mollaghasemi, M., and Richie, S., “Gap-Based Estimation: Choosing the Smoothing Parameters for Probabilistic and General Regression Neural Networks”, Proceedings of the 2006 IEEE-INNS-ENNS International Joint Conference on Neural Networks, pp. 1870–1877, 2006.