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Conference Paper
M. J. Johnson, Mollaghasemi, M., Georgiopoulos, M., and McGinnis, M., “A methodology for human behavior modeling in computer generated forces”, in Industrial Engineering Research Conference 2001 (IERC 2001), Dallas, TX, 2001.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “MO-GART: Multi-Objective Optimization of ART Architectures”, in 2008 IEEE Congress on Evolutionary Computation (IEEE CEC 2008), Hong Kong, 2008.
T.Rubio, Zhang, T., Georgiopoulos, M., and Kaylani, A., “Multi-Objective Evolutionary Optimization of Exemplar-Based Classifiers: A PNN Test Case”, in International Joint Conference on Neural Networks (IJCNN), San Jose, CA, 2011.
Journal Article
J. Secretan, Georgiopoulos, M., Maidhof, I., Shibly, P., and Hecker, J., “Methods for Parallelizing the Probabilistic Neural Network on a Beowulf Cluster Computer”, 2006.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G. C., “M-GFAM:An Elegant Approach to Genetically Optimize Fuzzy ARTMAP Neural Network Architectures”, Proceedings of the 8th International Conference on Natural Computing (ICNC 2007),part of the 10th Joint Conference on Information Sciences (JCIS 2007), pp. 1617-1623, 2007.
A. Henninger, Gonzalez, A., Georgiopoulos, M., and DeMara, R., “Modeling Semi-Automated Forces with Neural Networks: Performance Improvement through a Modular Approach”, 2000.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “MO-GART: An adaptive multi-objective approach to evolving ART architectures”, IEEE Transactions on Neural Networks, vol. 21, pp. 529-550, 2010.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “MO-GART: An adaptive multi-objective approach to evolving ART architectures”, IEEE Transactions on Neural Networks, vol. 21, pp. 529-550, 2010.
X. Rui, Anagnostopoulos, G. C., and II, W. D., “Multiclass Cancer Classification Using Semisupervised Ellipsoid ARTMAP and Particle Swarm Optimization with Gene Expression Data”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 4., pp. 65–77, 2007.
T. Zhang, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Multi-Objective Model Selection via Racing”, IEEE Transactions on Cybernetics, vol. 46, no. 8, pp. 1863-1876, 2015.
E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Multiple mobile user tracking with neural network-based adaptive array antennas”, SPIE Conference on Digital Wireless Communications, pp. 88–97, 1999.
C. Christodoulou, Georgiopoulos, M., and Zooghby, E. A., “Multiple Source Angle of Arrival Estimation using Neural-Network-based Smart Antennas”, Proceedings SPIE; Conference on Digital Wireless Communications II, pp. 94–99, 2000.
E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Multiple sources neural network direction finding with arbitrary separations”, IEEE-APS Conference on Antennas and Propagation for Wireless Communications, pp. 57–60, 1998.
C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “Multi-Task Classification Hypothesis Space with Improved Generalization Bounds ”, IEEE Transactions on Neural Networks and Learning Systems, vol. accepted for publication (acceptance was communicated in July 2014), 2014.
C. Li, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Multi-Task Classification Hypothesis Space with Improved Generalization Bounds”, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 7, pp. 1468-1479, 2015.