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S

J. Secretan, Koufakou, A., and Georgiopoulos, M., “APHID: A practical architecture for high-performance, privacy preserving, data-mining”, in DMIN 2009, Las Vegas,NV, 2009.

J. Secretan, Lawson, M., and Boloni, L., “Brokering Algorithms for Composing Low Cost Distributed Storage Resources”, 2007.

J. Secretan, Georgiopoulos, M., and Castro, J., “A Privacy Preserving Probabilistic Neural Network for Horizontally Partitioned Databases”, 2007.

J. Secretan, Georgiopoulos, M., Maidhof, I., Shibly, P., and Hecker, J., “Methods for Parallelizing the Probabilistic Neural Network on a Beowulf Cluster Computer”, 2006.

J. Secretan, Castro, J., Chadha, A., Huber, B., Tapia, J., Georgiopoulos, M., Anagnostopoulos, G., and Richie, S., “Pipelining of ART architectures (FAM, EAM, GAM) without match-tracking (MT)”, in 2005 Artificial Neural Networks in Engineering, St. Louis, MI, 2005.

J. Secretan, Georgiopoulos, M., Anagnostopoulos, G. C., Tapia, J., Chadha, A., and Huber, B., “Parallelizing the Fuzzy ARTMAP Algorithm on a Beowulf Clusters”, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2005), pp. 475–480, 2005.

C. Sentelle, Anagnostopoulos, G. C., and Georgiopoulos, M., “An efficient active set method for SVM training without singular inner problems”, in the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2009), Atlanta, GA, 2009.

C. Sentelle and G.C. Anagnostopoulos, G. M., “A Fast Revised Simplex Method for SVM Training”, ICPR, 2009.

C. Sentelle, Hong, S. L., Anagnostopoulos, G. C., and Georgiopoulos, M., “A fuzzy gap statistic for Fuzzy C-Means”, Proceedings of the 11th IASTED International Conference on Artificial, 2007.

C. Sentelle, Georgiopoulos, M., Anagnostopoulos, G. C., and Young, C., “On extending the SMO algorithm sub-problem”, Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2007.

C. Sentelle, Hong, S. L., Georgiopoulos, M., and Anagnostopoulos, G. C., “A Fuzzy Gap-statistic for Fuzzy C-Means”, in The 11th IASTED International Conference on Artificial Intelligence and Soft Computing (ASC 2007), Palma de Malorca, Spain, 2007.

C. Sentelle, Anagnostopoulos, G. C., and M. Georgiopoulos, R. DeMara, “A Simple Method for Solving the SVM Regularization Path for Semi-Definite Kernels”, IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 4, pp. 709-722, 2016.

N. Shorter and Kasparis, T., “3D Reconstruction of Irregular Spaced LIDAR”, Proceedings of the 6th WSEAS International Conference on Systems Theory and Scientific Computation, 2006.

N. Shorter and Kasparis, T., “Fuzzy SART Clustering for 3D Reconstruction from Irregular LIDAR Data”, vol. 2.8, pp. 1122 – 1129, 2006.

S. E. Skarman, Georgiopoulos, M., and Gonzalez, A. J., “Short-term electrical load forecasting using a fuzzy ARTMAP neural network”, Conference on Applications and Science of Computational Intelligence, pp. 181-191, 1998.

B. O. Smith, Georgiopoulos, M., and Belkerdid, M., “Comparison of BCH and convolutional codes in direct sequence spread spectrum multiple access packet radio networks”, in MILCOM 91, McLean, Virginia, 1991.

T

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.

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J. J. Vargas, DeMara, R. F., Gonzalez, A. J., Georgiopoulos, M., and Marshall, H., “PDU Bundling and Replication for Reduction of Distributed Simulation Communication Traffic”, Journal of Defense Modeling and Simulation, vol. 1.3, pp. 171–183, 2004.

A. Vartak, Georgiopoulos, M., and Anagnostopoulos, G. C., “On-line Gaussae Newton-based learning for fully recurrent neural networks”, Nonlinear Analysis, vol. 63, pp. e867–e876, 2005.

S. Verzi, Heileman, G., Georgiopoulos, M., and Healy, M., “Hierarchical ARTMAP”, Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp. 41–46, 2008.

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.

S. Verzi, Heileman, G., Georgiopoulos, M., and Anagnostopoulos, G. C., “Universal approximation with Fuzzy ART and Fuzzy ARTMAP”, Neural Networks, pp. 1987–1992, 2003.

S. Verzi, Heileman, G. L., Georgiopoulos, M., and Anagnostopoulos, G. C., “Off-line structural risk minimization and BARTMAP-S”, in the 2002 International Joint Conference on Neural Networks, Honolulu, Hawaii, 2002.

S. Verzi, Heileman, G., Georgiopoulos, M., and Anagnostopoulos, G. C., “Off-line structural risk minimization and BARTMAP-S”, Neural Networks, pp. 2533–2538, 2002.

S. J. Verzi, Heileman, G. L., Georgiopoulos, M., and Healy, M. J., “Rademacher penalization applied to Fuzzy ARTMAP and Boosted ARTMAP”, Proceedings of the International Joint Conference on Neural Networks, pp. 1191–1196, 2001.

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.

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R. C. Watkins, Reynolds, K. M., DeMara, R., Georgiopoulos, M., Gonzalez, A., and Eaglin, R., “TRACKING DIRTY PROCEEDS: EXPLORING DATA MINING TECHNOLOGIES AS TOOLS TO INVESTIGATE MONEY LAUNDERING”, Police Practice and Research, vol. 4.2, pp. 163–178, 2003.

Y

Y.Huang, M. Georgiopoulos, R. DeMara,, and G.C. Anagnostopoulos, M. Georgiopoulos, “Accelerated Learning of Generalized Sammon Mappings”, in International Joint Conference on Neural Networks (IJCNN), San Jose, CA, 2011.

C. Young, Georgiopoulos, M., Hagen, S., Geiger, C., Dagley-Falls, M., Islas, A., Ramsey, P., Lancey, P., Forde, D., and Bradbury, E., “Improving Student Learning in Calculus through Applications”, International Journal of Mathematical Education in Science and Technology, vol. 42, pp. 591-604, 2011.

Z

T. Zhang, Borrero, G., and Georgiopoulos, M., “A Winner-Take-All Methodology: Finding the Best Evolutionary Algorithm for the Global Optimization of Functions”, Genetic and Evolutionary Computation Conference. Philadelphia, July 7th-July 11th, pp. 1515-1516, 2012.

T. Zhang, Georgiopoulos, M., and Anagnostopoulos, G. C., “S-RACE: A Multi-objective Racing Algorithm”, GECCO 2013, Proceedings of the fifteenth annual conference on Genetic and evolutionary computation conference. Amsterdam, the Netherlands, July 6-10, pp. 1565-1572, 2013.

T. Zhang, Georgiopoulos, M., and Anagnostopoulos, G. C., “Online Model Racing Based on Extreme Performance”, in GECCO 2014, Vancouver, Canada, July 12-16, 2014, accepted for publication, 2014.

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.

T. Zhang, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Pareto Optimal Selection via SPRINT-Race”, IEEE Transactions on Cybernetics, vol. 48, no. 2, pp. 596-610, 2018.

M. Zhong, Georgiopoulos, M., and Anagnostopoulos, G. C., “A k -norm pruning algorithm for decision tree classifiers based on error rate estimation”, Machine Learning, vol. 71, pp. 55-88, 2008.

M. Zhong, Georgiopoulos, M., and Anagnostopoulos, G. C., “Experiments with an Innovative Tree Pruning Algorithm”, in IASTED International Conference on Artificial Intelligence and Applications, Innsbruck, Innsbruck, 2007.

M. Zhong, Georgiopoulos, M., and Anagnostopoulos, G. C., “k-Norm Misclassification Rate Estimation for Decision Trees”, Proceedings of the 11th IASTED International Conference on Artificial Intelligence and Soft Computing (ASC 2007), pp. 163–168, 2007.

M. Zhong, Rosander, B., Georgiopoulos, M., Anagnostopoulos, G. C., Mollaghasemi, M., and Richie, S., “Experiments with Safe micro-ARTMAP: Effect of the Network Parameters on the Network Performance”, Neural Networks, vol. 20.2, pp. 245–259, 2007.

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, Rosander, B., Georgiopoulos, M., Anagnostopoulos, G., Mollaghasemi, M., and Richie, S., “Experiments with Safe Micro-ARTMAP: Effect of the Network Parameters on the Network Performance”, in WCCI 2006, Vancouver, Canada, 2006.

M. Zhong, Rosander, B., Georgiopoulos, M., Anagnostopoulos, G. C., Mollaghasemi, M., and Richie, S., “Experiments with Safe ARTMAP and Comparisons to Other ART Networks”, Proceedings of the 2006 IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2006), pp. 720–727, 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.

M. Zhong, Rosander, B., Georgiopoulos, M., Anagnostopoulos, G., Mollaghasemi, M., and Richie, S., “Experiments with Micro-ARTMAP: Effect of the Network Parameters on the Network Performance”, in 2005 Artificial Neural Networks in Engineerin, St. Louis, MI, 2005.

M. Zhong, Hecker, J., Maidhoff, I., Shibly, P., Georgiopoulos, M., Anagnostopoulos, G., and Mollaghasemi, M., “Probabilistic Neural Network: Comparisons of the Cross-Validation Approach and a Fast Heuristic to choose the Smoothing Parameters”, in 2005 Artificial Neural Networks in Engineering, St. Louis, MI, 2005.

A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “A Neural Network-Based Smart Antenna for Multiple Source Tracking”, IEEE Transactions on Antennas and Propagation, vol. 48.5, pp. 768–776, 2000.

E. A. H. Zooghby, Christodoulou, C., and Georgiopoulos, M., “A neural-network-based linearly constrained minimum variance beamformer”, Microwave and Optical Technology Letters, vol. 21.6, pp. 451–455, 1999.

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.

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.

E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Radial basis function neural network algorithm for adaptivebeamforming in cellular communication systems”, IEEE-APS Conference on Antennas and Propagation for Wireless Communications, pp. 53–56, 1998.

A. H. E. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Adaptive interference cancellation with neural networks”, in 1998 Virginia Tech Symposium on Wireless Personal Communications, 1998.

E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Adaptive interference cancellation in circular arrays with radialbasis function neural networks”, IEEE Antennas and Propagation Society International Symposium, 1998.

E. A. H. Zooghby, Christodoulou, C., and Georgiopoulos, M., “Neural Network-Based Adaptive Beamforming for One- and Two-Dimensional Antenna Arrays”, IEEE Transactions on Antennas and Propagation, vol. 46.1, pp. 1891–1893, 1998.

E. A. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Neural Network based beamforming for interference cancellation”, Conference on Applications and Science of Computational Intelligence, pp. 420–429, 1998.

A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “A novel approach to adaptive nulling with neural networks”, Southeastcon, pp. 216–219, 1998.

A. H. E. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Neural network-based adaptive beamforming for one- and two-dimensional antenna arrays”, IEEE Transactions on Antennas and Propagation, vol. 46, pp. 1891-1893, 1998.

E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Performance of Radial-Basis Function Networks for Direction of Arrival Estimation with Antenna Arrays”, IEEE Transactions on Antennas and Propagation, vol. 45.11, pp. 1611–1617, 1997.

A. E. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Neural network approach for direction of arrival estimation”, in Proceedings SPIE; Conference of Applications and Science of, Orlando, FL, 1997.

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