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2014
C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “Conic Multi-Task Classification”, in ECML PKDD 2014, Nancy, France, September 15-19, 2014.
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.
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.
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.
C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “Pareto-Path Multi-task Multiple Kernel Learning”, IEEE Transactions on Neural Networks and Learning Systems, vol. accepted for publication (acceptance was communicated in June 2014), 2014.
C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “A Unifying Framework for Typical Multitask, Multiple Kernel Learning Problems”, IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 7, pp. 1287-1297, 2014.
2013
L. Massi, Georgiopoulos, M., Young, C. Y., Ford, C. M., Lancey, P., Bhati, D., and Small, K. A., “Internships and Undergraduate Research: Impact, Support, and Institutionalization of an NSF S-STEM Program through Partnerships with Industry and Funding from Federal and Local Workforce Agencies”, Proceedings of the 120th ASEE Conference and Exposition. Atlanta, GA, June 23-26, 2013.
C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “Kernel-based Distance Metric Learning in the Output Space”, in International Joint Conference on Neural Networks (IJCNN), Dallas, TX, August 04-09, 2013.
Y. Huang, Li, C., Georgiopoulos, M., and Anagnostopoulos, G. C., “Reduced Rank Local Distance Metric Learning”, in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML and PKDD 2013), Prague, Czech Republic, September 23-27, 2013.
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.
2012
L. Massi, Lancey, P., Nair, U., Straney, R., Georgiopoulos, M., and Young, C., “Engineering and Computer Science Community College Transfers and Native Freshmen Students: Relationships Among Participation in Extra-Curricular and Co-Curricular Activities, Connecting to the University Campus, and Academic Success”, in Frontiers in Education Conference, Seattle, WA, October 3-6, 2012.
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.
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.
M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, Performance Evaluation, vol. 68, pp. 361-384, 2011.
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.
2010
J. Secretan, Koufakou, A., Georgiopoulos, M., and Cardona, K., “APHID: An architecture for private, high-performance integrated data-mining”, Journal of Future Generation Computer Systems, vol. 26, pp. 891-904, 2010.
A. Koufakou and Georgiopoulos, M., “A fast outlier detection strategy for distributed high dimensional datasets with mixed attributes”, Data Mining and Knowledge Discovery, vol. 20, pp. 259-289, 2010.
R. Miguez, Georgiopoulos, M., and Kaylani, A., “A Genetically Engineered Probabilistic Neural Network”, Nonlinear Analysis: Theory, Methods & Applications, vol. 73, pp. 1783-1791, 2010.
C. Puklavage, Pirela, A., Gonzalez, A. J., and Georgiopoulos, M., “Imitating personalized expressions through an Avatar using Machine Learning”, in Proceedings of the 23rd International FLAIRS conference, 2010.
M. Dagley-Falls, Georgiopoulos, M., and Young, C., “Influencing sense of community in a STEM living-learning community: An NSF STEP funded project”, in Proceedings of the 2010 ASEE Conference and Exposition, 2010.
M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, in the 25th International Symposium on Computer and Information Sciences, London, UK, 2010.
M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, Performance Evaluation, 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.
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. Koufakou, Secretan, J., and Georgiopoulos, M., “Non-derivable itemsets for fast outlier detection in large high dimensional categorical data”, Knowledge and Information Systems, pp. 1-29, 2010.
R. Ramirez-Padron, Foregger, D., Manuel, J., Georgiopoulos, M., and Mederos, B., “Similarity Kernels for Nearest Neighbor-based Outlier Detection”, Lecture Notes in Computer Science, vol. 6065/2010, pp. 159-170, 2010.
2009
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “AG-ART: An Adaptive Method of Evolving ART Architectures”, Neurocomputing, vol. 72, pp. 2079-2092, 2009.
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.
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.
M. Georgiopoulos, DeMara, R. F., Gonzalez, A. J., Wu, A. S., Mollaghasemi, M., Gelenbe, E., Kysilka, M., Secretan, J., Sharma, C. A., and Alnsour, A. J., “A Sustainable Model for Integrating Current Topics in Machine Learning Research in the Undergraduate Curriculum”, IEEE Transactions on Education, vol. 52, pp. 503-512, 2009.
2008
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.
D. Charalampidis, Anagnostopoulos, G. C., Kasparis, T., and Georgiopoulos, M., “Classification of noisy patterns using ARTMAP-based neural networks”, Proceedings SPIE; Conference on Visual Information Processing IX, pp. 2-13, 2008.
A. Koufakou, Georgiopoulos, M., and Anagnostopoulos, G. C., “Detecting Outliers in High-Dimensional Datasets with Mixed Attributes”, International Conference on Data Mining (DMIN 2008), 2008.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “Efficient Evolution of ART Neural Networks”, in 2008 IEEE Congress on Evolutionary Computation (IEEE CEC 2008), 2008.
A. Koufakou, Secretan, J., Reeder, J., Cardona, K., and Georgiopoulos, M., “Fast Parallel Outlier Detection for Categorical Datasets using MapReduce”, IEEE World Congress on Computational Intelligence (WCCI), 2008.
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.
J. Reeder, Gita, S., Georgiopoulos, M., and Anagnostopoulos, G. C., “Intelligent Trading Agents for Massively Multi-player Game Economies”, Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference, pp. 102–107, 2008.
J. Reeder, Miguez, R., Sparks, J., Georgiopoulos, M., and Anagnostopoulos, G. C., “Interactively Evolved Modular Neural Networks for Game Agent Control”, IEEE Symposium on Computational Intelligence and Games (CIG 08, pp. 167–174, 2008.
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.
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.
D. Charalampidis, Kasparis, T., Jones, L., and Georgiopoulos, M., “Use of multifractals to detect anomalous propagation (AP) in weather radar”, Proceedings SPIE; Conference on Signals and Data Processing of Small Targets, pp. 13–22, 2008.
2007
J. Castro, Georgiopoulos, M., and Secretan, J., “Analyzing the Fuzzy ARTMAP Matchtracking mechanism with Co-Objective Optimization Theory”, Proceedings of the International IEEE-INNS-ENNS Joint Conference on Neural Networks (IJCNN), pp. 743–748, 2007.
M. Gul, Catbas, F. N., and Georgiopoulos, M., “Application of Pattern Recognition Techniques to Identify Structural Change in a Laboratory Specimen”, in he SPIE Smart Structures and Materials & Nondestructive Evaluation and Health Monitoring Conference, San Diego, CA, 2007.
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, 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.
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., 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, 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.
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.
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-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-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.
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.
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.
J. Castro, Secretan, J., Georgiopoulos, M., DeMara, R., Anagnostopoulos, G. C., and Gonzalez, A., “Pipelining of Fuzzy ARTMAP without Matchtracking: Correctness,Performance Bound and Beowulf Evaluation”, Neural Networks, vol. 20.1, pp. 109–128, 2007.
J. Secretan, Georgiopoulos, M., and Castro, J., “A Privacy Preserving Probabilistic Neural Network for Horizontally Partitioned Databases”, 2007.
A. Koufakou, Ortiz, E., Georgiopoulos, M., Anagnostopoulos, G. C., and Reynolds, M. K., “A scalable and efficient otlier detection strategy for categorical data”, in Annual IEE International Conference on Tools with Artificial Intelligence, 2007 (ICTAI 2007),, Patras, Greece, 2007.
A. Koufakou, Ortiz, E., Georgiopoulos, M., Anagnostopoulos, G. C., and Reynolds, K., “A Scalable and Efficient Outlier Detection Strategy for Categorical Data”, International Conference on Tools with Artificial Intelligence (ICTAI), 2007.
A. Gonzalez, Georgiopoulos, M., and DeMara, R., “Using Context-Based Neural Networks to Maintain Coherence Among Entities’ States in a Distributed Simulation”, The Journal of Defense Modeling and Simulation, vol. 4, pp. 147-172, 2007.
A. Gonzalez, Georgiopoulos, M., and DeMara, R., “Using context-based neural networks to maintain coherence in distributed simulations”, The Journal of Defense Modeling and Simulation, vol. 4, pp. 417-172, 2007.
2006
O. Kursun, Koufakou, A., Wakchaure, A., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “Answer: approximate Name Search with Errors in Large Databases by a Novel Approach Based on Prefix-dictionary”, International Journal on Artificial Intelligence Tools, vol. 15.5, pp. 839–848, 2006.
M. Georgiopoulos, Gelenbe, E., DeMara, R., Gonzalez, A., Mollaghasemi, M., Wu, A., Russell, I., Anagnostopoulos, G., and Secretan, J., “Assessing and Evaluating our progress on the CRCD Experiences at the University of Central Florida: An NSF Project”, in 2006 ASEE, Chicago, Illinois, 2006.
M. Georgiopoulos, Gelenbe, E., DeMara, R., Gonzalez, A., Mollaghasemi, M., Wu, A., Russell, I., Anagnostopoulos, G., and Secretan, J., “Assessing and Evaluating our progress on the CRCD Experiences at the University of Central Florida: An NSF Project”, 2006.
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.
A. Koufakou, Weihs, N., Georgiopoulos, M., and Al-Daraiseh, A., “Comparisons of Gaussian ARTMAP and Distributed Gaussian ARTMAP Classifiers - The Category Proliferation Problem”, Evolutionary Programming,Complex Systems and Artificial Life also presented at the 2006 Artificial Neural Networks in Engineering (ANNIE), vol. 16, pp. 695–704, 2006.
A. Koufakou, Weihs, N., Georgiopoulos, M., and Al-Daraiseh, A., “Comparisons of Gaussian ARTMAP and Distributed Gaussian ARTMAP: The Category Proliferation problem”, in ANNIE 2006, St. Louis, Missouri, 2006.
O. Kursun, Koufakou, A., Chen, B., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “A Dictionary-Based Approach to Fast and Accurate Name Matching in Large Law Enforcement Databases”, IEEE Intelligence and Security Informatics (ISI) Conference, pp. 72–82, 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, 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, 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.
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.
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.
H. K. Fernlund, Gonzalez, A. J., Georgiopoulos, M., and DeMara, R., “Learning tactical human behavior through observation of human performance”, Cybernetics–Part B: Cybernetics,Man,IEEE Transactions on Systems, vol. 36.1, pp. 128–140, 2006.
J. Secretan, Georgiopoulos, M., Maidhof, I., Shibly, P., and Hecker, J., “Methods for Parallelizing the Probabilistic Neural Network on a Beowulf Cluster Computer”, 2006.
G. C. Anagnostopoulos, Georgiopoulos, M., Ports, K., Richie, S., Cardinale, N., White, M., Kepuska, V., Chan, P. K., Wu, A., and Kysilka, M., “Project EMD-MLR: Educational Materials Development and Research in Machine Learning for Undergraduate students”, in 2006 ASEE, Chicago, Illinois, 2006.
2005
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.
M. Georgiopoulos, Gelenbe, E., DeMara, R., Gonzalez, A., Kysilka, M., Mollaghasemi, M., Wu, A., Russell, I., Anagnostopoulos, G., and Secretan, J., “CRCD Experiences at the University of Central Florida: An NSF Project”, in the ASEE 2005 Annual Conference and Exposition, Portland Oregon, 2005.
J. Castro, Georgiopoulos, M., DeMara, R., and Gonzalez, A., “Data-partitioning using the Hilbert space filling curves Effect on the speed of convergence of Fuzzy ARTMAP for large database problems”, Neural Networks, vol. 18, pp. 967-984, 2005.
J. Castro, Georgiopoulos, M., DeMara, R., and Gonzalez, A., “Data-partitioning using the Hilbert space filling curves: Effect on the speed of convergence of Fuzzy ARTMAP for large database problems”, Neural Networks, vol. 18.7, pp. 967–984, 2005.
K. Reynolds, Kursun, O., Eaglin, R., Chen, B., and Georgiopoulos, M., “Development of an Artificial Intelligent System for detection and visualization of auto theft recovery patterns”, in Computational Intelligence Conference on Homeland Security and Public Safety (CIHSPS, 2005), Orlando, FL, 2005.
L. Quang, Anagnostopoulos, G., Georgiopoulos, M., and Ports, K., “An experimental comparison of semi-supervised ARTMAP architectures, GCS, and GNC Classifiers”, in 2005 International Joint Conference on Neural Networks, Montreal, Quebec, 2005.
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.
J. Reeder, Georgiopoulos, M., Castro, J., Burns, S., Anagnostopoulos, G., and Mollaghasemi, M., “Hilbert Space Filling Curve Nearest Neighbor”, in The ISAS and CITSA 2005, Orlando, FL, 2005.
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.
J. Castro, Georgiopoulos, M., Secretan, J., DeMara, R., Anagnostopoulos, G. C., and Gonzalez, A., “Parallelization of Fuzzy ARTMAP to improve its convergence speed: The network partitioning approach and the data partitioning approach”, Nonlinear Analysis: Theory,Methods and Applications, vol. 63.5-7, pp. e877–e889, 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.
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.
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.
G. C. Anagnostopoulos, Georgiopoulos, M., Ports, K., Richie, S., Cardinale, N., White, M., Kepuska, V., Chan, P. K., Wu, A., and Kysilka, M., “Project EMD-MLR: Educational Materials Development and Research in Machine Learning for Undergraduate students”, in the ASEE 2005 Annual Conference and Exposition, Portland, Oregon, 2005.
2004
A. J. Gonzalez, Gerber, W. J., DeMara, R. F., and Georgiopoulos, M., “Context-driven Near-term Intention Recognition”, Journal of Defense Modeling and Simulation, vol. 1.3, pp. 153–170, 2004.
M. Georgiopoulos, Castro, J., Gelenbe, E., DeMara, R., Gonzalez, A., and Kysilka, M., “CRCD Experiences at the University of Central Florida: An NSF Project”, Proceedings of the ASEE 2004 Annual Conference and Exposition, 2004.
J. Castro, Georgiopoulos, M., DeMara, R., and Gonzalez, A., “A data partitioning approach to speed the Fuzzy ARTMAP algorithm using the Hilbert space-filling curve”, pp. 2367–2372, 2004.
J. Klodzinski, Al-Daraiseh, A., Georgiopoulos, M., and Al-Deek, H. M., “Development of a java applet for generating truck trips from freight data”, Transportation Research Record No. 1870, pp. 10–17, 2004.
K. Reynolds, Kursun, O., Georgiopoulos, M., and Eaglin, R., “Development of an Artificial Intelligence Clustering Algorithm to Detect Auto Theft Recovery Patterns”, in GIS Symposium 2004, Troy, AL, 2004.
M. Mollaghasemi, Georgiopoulos, M., Cope, D., Donnelly, A., and Steele, M., “Educating Middle and High School Students in Space Operations”, in the 2004 Winter Simulation Conference, Washington, DC, 2004.
A. Meyer-Base, Jancke, K., Wissmuller, A., and Georgiopoulos, M., “Fast K-dimensional tree-structured vector quantization encoding method for image compression”, Optical Engineering Letters, vol. 43, pp. 1012-1013, 2004.
K. Carr, Cannava, K., Pescatore, R., Georgiopoulos, M., and Anagnostopoulos, G., “Fast Stable and on-line training of Fuzzy ARTMAP using a novel, conservative, slow learning strategy”, in ANNIE 2004 conference, St. Louis, MI, 2004.
K. Carr, Cannava, K., Pescatore, R., Georgiopoulos, M., and Anagnostopoulos, G. C., “Fast Stable and on-line training of Fuzzy ARTMAP using a novel,conservative,slow learning strategy”, Neural Networks, pp. 63–69, 2004.

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